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References

Published online by Cambridge University Press:  28 July 2022

Edited by
Michael A. Skeide
Michael A. Skeide
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Max Planck Institute for Human Cognitive and Brain Sciences
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The Cambridge Handbook of Dyslexia and Dyscalculia , pp. 465 - 610
Publisher: Cambridge University Press
Print publication year: 2022

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References

Primary Sources

71st World Health Assembly. 2018. 21–26 May 2018. https://ec.europa.eu/info/events/sustainable-development-goals/71st-world-health-assembly-2018-may-21_de.Google Scholar
Aarnoudse-Moens, C. S. H., Weisglas-Kuperus, N., van Goudoever, J. B., and Oosterlaan, J.. 2009. ‘Meta-Analysis of Neurobehavioral Outcomes in Very Preterm and/or Very Low Birth Weight Children’. Pediatrics 124 (2): 717–28.CrossRefGoogle ScholarPubMed
Abreu-Villaça, Y., Seidler, F. J., Tate, C. A., Cousins, M. M., and Slotkin, T. A.. 2004. ‘Prenatal Nicotine Exposure Alters the Response to Nicotine Administration in Adolescence: Effects on Cholinergic Systems during Exposure and Withdrawal’. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology 29 (5): 879–90.CrossRefGoogle ScholarPubMed
Ackerman, J. P., Riggins, T., and Black, M. M.. 2010. ‘A Review of the Effects of Prenatal Cocaine Exposure among School-Aged Children’. Pediatrics 125 (3): 554–65.CrossRefGoogle ScholarPubMed
Ahmad, K., Casey, M., and Bale, T.. 2002. ‘Connectionist Simulation of Quantification Skills’. Connection Science 14 (3): 165–201.CrossRefGoogle Scholar
Ahmed, W. 2018. ‘Developmental Trajectories of Math Anxiety during Adolescence: Associations with STEM Career Choice’. Journal of Adolescence 67 (August): 158–66.CrossRefGoogle ScholarPubMed
Alarcón, M., DeFries, J. C., Light, J. G., and Pennington, B. F.. 1997. ‘A Twin Study of Mathematics Disability’. Journal of Learning Disabilities 30 (6): 617–23.CrossRefGoogle ScholarPubMed
Alexander, R. 1982. ‘Implementation: Does a Literature Add Up to a Theory?’ Journal of the American Planning Association 48 (1): 132–55.Google Scholar
Allik, J., and Tuulmets, T.. 1991. ‘Occupancy Model of Perceived Numerosity’. Perception & Psychophysics 49 (4): 303–14.CrossRefGoogle ScholarPubMed
Al-Saleh, I., Shinwari, N., Nester, M., et al. 2008. ‘Longitudinal Study of Prenatal and Postnatal Lead Exposure and Early Cognitive Development in Al-Kharj, Saudi Arabia: A Preliminary Results of Cord Blood Lead Levels’. Journal of Tropical Pediatrics 54 (5): 300–7.CrossRefGoogle ScholarPubMed
American College of Obstetricians and Gynecologists (ACOG). 2004. ‘Neonatal Encephalopathy and Cerebral Palsy: Executive Summary’. Obstetrics and Gynecology 103 (4): 780–1.Google Scholar
American Psychiatric Association. 2013. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). American Psychiatric Publishing.Google Scholar
Amin-Zaki, L., Elhassani, S., Majeed, M. A., et al. 1976. ‘Perinatal Methylmercury Poisoning in Iraq’. American Journal of Diseases of Children 130 (10): 1070–6.Google ScholarPubMed
Amin-Zaki, L., Majeed, M. A., Greenwood, M. R., et al. 1981. ‘Methylmercury Poisoning in the Iraqi Suckling Infant: A Longitudinal Study over Five Years’. Journal of Applied Toxicology: JAT 1 (4): 210–14.CrossRefGoogle ScholarPubMed
Anderson, J. R., Betts, S, Ferris, J. L., and Fincham, J. M.. 2011. ‘Cognitive and Metacognitive Activity in Mathematical Problem Solving: Prefrontal and Parietal Patterns’. Cognitive, Affective & Behavioral Neuroscience 11 (1): 52–67.CrossRefGoogle ScholarPubMed
Anderson, J. W., Johnstone, B. M., and Remley, D. T.. 1999. ‘Breast-Feeding and Cognitive Development: A Meta-Analysis’. The American Journal of Clinical Nutrition 70 (4): 525–35.CrossRefGoogle ScholarPubMed
Anjari, M., Srinivasan, L., Allsop, J. M., et al. 2007. ‘Diffusion Tensor Imaging with Tract-Based Spatial Statistics Reveals Local White Matter Abnormalities in Preterm Infants’. NeuroImage 35 (3): 1021–7.CrossRefGoogle ScholarPubMed
Anobile, G., Stievano, P., and Burr, D. C.. 2013. ‘Visual Sustained Attention and Numerosity Sensitivity Correlate with Math Achievement in Children’. Journal of Experimental Child Psychology 116 (2): 380–91.CrossRefGoogle ScholarPubMed
Ansari, D. 2007. ‘Does the Parietal Cortex Distinguish between “10,” “Ten,” and Ten Dots?’ Neuron 53 (2): 165–7. https://doi.org/10.1016/j.neuron.2007.01.001.CrossRefGoogle ScholarPubMed
Ansari, D 2008. ‘Effects of Development and Enculturation on Number Representation in the Brain’. Nature Reviews. Neuroscience 9 (4): 278–91.CrossRefGoogle ScholarPubMed
Ansari, D 2010. ‘Neurocognitive Approaches to Developmental Disorders of Numerical and Mathematical Cognition: The Perils of Neglecting the Role of Development’. Learning and Individual Differences 20 (2): 123–9.CrossRefGoogle Scholar
Ansari, D. and Dhital, B.. 2006. ‘Age-Related Changes in the Activation of the Intraparietal Sulcus during Nonsymbolic Magnitude Processing: An Event-Related Functional Magnetic Resonance Imaging Study’. Journal of Cognitive Neuroscience 18 (11): 1820–8. https://doi.org/10.1162/jocn.2006.18.11.1820.CrossRefGoogle ScholarPubMed
Ansari, D., Garcia, N., Lucas, E., Hamon, K., and Dhital, B.. 2005. ‘Neural Correlates of Symbolic Number Processing in Children and Adults’. Neuroreport 16 (16): 1769–73.CrossRefGoogle ScholarPubMed
Araki, M., Nagata, K., Satoh, Y., et al. 2002. ‘Developmentally Regulated Expression of Neuro-p24 and Its Possible Function in Neurite Extension’. Neuroscience Research 44 (4): 379–89. https://doi.org/10.1016/s0168-0102(02)00156-6.CrossRefGoogle ScholarPubMed
Araújo, S., Reis, A., Petersson, K. M., and Faísca, L.. 2015. ‘Rapid Automatized Naming and Reading Performance: A Meta-Analysis’. Journal of Educational Psychology 107 (3): 868–83. https://doi.org/10.1037/edu0000006.CrossRefGoogle Scholar
Archer, K., Pammer, K., and Vidyasagar, T. R.. 2020. ‘A Temporal Sampling Basis for Visual Processing in Developmental Dyslexia’. Frontiers in Human Neuroscience 14 (July): 213.CrossRefGoogle ScholarPubMed
Arciuli, J., and Simpson, I. C.. 2012. ‘Statistical Learning Is Related to Reading Ability in Children and Adults’. Cognitive Science 36 (2): 286–304.CrossRefGoogle ScholarPubMed
Arnold, E. M., Goldston, D. B., Walsh, A. K., et al. 2005. ‘Severity of Emotional and Behavioral Problems among Poor and Typical Readers’. Journal of Abnormal Child Psychology 33 (2): 205–17.CrossRefGoogle ScholarPubMed
Arsalidou, M., Pawliw-Levac, M., Sadeghi, M., and Pascual-Leone, J.. 2018. ‘Brain Areas Associated with Numbers and Calculations in Children: Meta-Analyses of fMRI Studies’. Developmental Cognitive Neuroscience 30: 239–50. https://doi.org/10.1016/j.dcn.2017.08.002.CrossRefGoogle ScholarPubMed
Arsalidou, M., and Taylor, M. J.. 2011. ‘Is 2+2=4? Meta-Analyses of Brain Areas Needed for Numbers and Calculations’. NeuroImage 54 (3): 2382–93.CrossRefGoogle Scholar
Artemenko, C., Soltanlou, M., Ehlis, A.-C., Nuerk, H.-C., and Dresler, T.. 2018. ‘The Neural Correlates of Mental Arithmetic in Adolescents: A Longitudinal fNIRS Study’. Behavioral and Brain Functions: BBF 14 (1): 5.CrossRefGoogle ScholarPubMed
Aschard, H., Chen, J, Cornelis, M. C., et al. 2012. ‘Inclusion of Gene-Gene and Gene-Environment Interactions Unlikely to Dramatically Improve Risk Prediction for Complex Diseases’. American Journal of Human Genetics 90 (6): 962–72.CrossRefGoogle ScholarPubMed
Ashcraft, M. H. 2002. ‘Math Anxiety: Personal, Educational, and Cognitive Consequences’. Current Directions in Psychological Science 11 (5): 181–85.CrossRefGoogle Scholar
Ashcraft, M. H., and Faust, M. W.. 1994. ‘Mathematics Anxiety and Mental Arithmetic Performance: An Exploratory Investigation’. Cognition and Emotion 8 (2): 97–125.CrossRefGoogle Scholar
Ashcraft, M. H., and Kirk, E. P.. 2001. ‘The Relationships among Working Memory, Math Anxiety, and Performance’. Journal of Experimental Psychology: General 130 (2): 224–37.Google ScholarPubMed
Ashcraft, M. H., and Krause, J. A.. 2007. ‘Working Memory, Math Performance, and Math Anxiety’. Psychonomic Bulletin & Review 14 (2): 243–8.CrossRefGoogle ScholarPubMed
Ashcraft, M. H., and Moore, A. M.. 2009. ‘Mathematics Anxiety and the Affective Drop in Performance’. Journal of Psychoeducational Assessment 27 (3): 197–205.CrossRefGoogle Scholar
Ashcraft, M. H., and Ridley, K. S.. 2005. ‘Math Anxiety and Its Cognitive Consequences’. In Campbell, D (ed.) Handbook of Mathematical Cognition, 315–27. Psychology Press.Google Scholar
Ashkenazi, S., Black, J. M., Abrams, D. A., Hoeft, F., and Menon, V.. 2013a. ‘Neurobiological Underpinnings of Math and Reading Learning Disabilities’. Journal of Learning Disabilities 46 (6). https://doi.org/10.1177/0022219413483174.CrossRefGoogle ScholarPubMed
Ashkenazi, S., Mark-Zigdon, N., and Henik, A.. 2009. ‘Numerical Distance Effect in Developmental Dyscalculia’. Cognitive Development 24 (4): 387–400.CrossRefGoogle Scholar
Ashkenazi, S., Rosenberg-Lee, M, Metcalfe, A. W. S., Swigart, A. G., and Menon, V.. 2013b. ‘Visuo-Spatial Working Memory is an Important Source of Domain-General Vulnerability in the Development of Arithmetic Cognition’. Neuropsychologia 51 (11): 2305–17.CrossRefGoogle ScholarPubMed
Ashkenazi, S., Rosenberg-Lee, M., Tenison, C., and Menon, V.. 2012. ‘Weak Task-Related Modulation and Stimulus Representations during Arithmetic Problem Solving in Children with Developmental Dyscalculia’. Developmental Cognitive Neuroscience 2 Suppl 1 (February): S152–66.CrossRefGoogle ScholarPubMed
Askenazi, S., and Henik, A.. 2010. ‘Attentional Networks in Developmental Dyscalculia’. Behavioral and Brain Functions: BBF 6 (January): 2.CrossRefGoogle ScholarPubMed
Ask, H., Idstad, M., Engdahl, B., and Tambs, K.. 2013. ‘Non-Random Mating and Convergence over Time for Mental Health, Life Satisfaction, and Personality: The Nord-Trøndelag Health Study’. Behavior Genetics 43 (2): 108–19.CrossRefGoogle ScholarPubMed
Assaf, Y., and Pasternak, O.. 2008. ‘Diffusion Tensor Imaging (DTI)-Based White Matter Mapping in Brain Research: A Review’. Journal of Molecular Neuroscience: MN 34 (1): 51–61.CrossRefGoogle ScholarPubMed
Aster, M. G. von, and Shalev, R. S.. 2007. ‘Number Development and Developmental Dyscalculia’. Developmental Medicine & Child Neurology. 49 (11): 868–73. https://doi.org/10.1111/j.1469-8749.2007.00868.x.Google Scholar
Aster, M. von, Kucian, K., Schweiter, M., and Martin, E.. 2005. ‘Rechenstörungen Im Kindesalter’. Monatsschrift Kinderheilkunde: Organ Der Deutschen Gesellschaft Fur Kinderheilkunde 153 (7): 614–22.Google Scholar
Aster, M. von, Weinhold, Z. M., and Horn, R.. 2006. Neuro-psychologische Testbatterie für Zahlenverarbeitung und Rechnen bei Kindern (ZAREKI-R). Har-court Test Services.Google Scholar
Astle, D. E., and Fletcher-Watson, S.. 2020. ‘Beyond the Core-Deficit Hypothesis in Developmental Disorders’. Current Directions in Psychological Science 29 (5): 431–7.CrossRefGoogle ScholarPubMed
Astley, S. J., Aylward, E. H., Olson, H. C., et al. 2009. ‘Functional Magnetic Resonance Imaging Outcomes from a Comprehensive Magnetic Resonance Study of Children with Fetal Alcohol Spectrum Disorders’. Journal of Neurodevelopmental Disorders 1 (1): 61–80.CrossRefGoogle ScholarPubMed
Atkinson, J., King, J., Braddick, O., et al. 1997. ‘A Specific Deficit of Dorsal Stream Function in Williams’ Syndrome’. Neuroreport 8 (8): 1919–22.CrossRefGoogle ScholarPubMed
Attout, L., and Majerus, S.. 2015a. ‘Working Memory Deficits in Developmental Dyscalculia: The Importance of Serial Order’. Child Neuropsychology 21 (4): 432–50. https://doi.org/10.1080/09297049.2014.922170.CrossRefGoogle ScholarPubMed
Attout, L., and Majerus, S. 2015b. ‘Working Memory Deficits in Developmental Dyscalculia: The Importance of Serial Order’. Child Neuropsychology: A Journal on Normal and Abnormal Development in Childhood and Adolescence 21 (4): 432–50.CrossRefGoogle ScholarPubMed
Attout, L., and Majerus, S. 2018. ‘Serial Order Working Memory and Numerical Ordinal Processing Share Common Processes and Predict Arithmetic Abilities’. British Journal of Developmental Psychology 36 (2): 285–98. https://doi.org/10.1111/bjdp.12211.CrossRefGoogle ScholarPubMed
Avancini, C., and Szűcs, D.. 2019. ‘Psychophysiological Correlates of Mathematics Anxiety’. In Mathematics Anxiety . Routledge. https://doi.org/10.4324/9780429199981-3.CrossRefGoogle Scholar
Axelrad, D. A., Bellinger, D. C., Ryan, L. M., and Woodruff, T. J.. 2007. ‘Dose-Response Relationship of Prenatal Mercury Exposure and IQ: An Integrative Analysis of Epidemiologic Data’. Environmental Health Perspectives 115 (4): 609–15.CrossRefGoogle ScholarPubMed
Bach, S., Richardson, U., Brandeis, D., Martin, E., and Brem, S.. 2013. ‘Print-Specific Multimodal Brain Activation in Kindergarten Improves Prediction of Reading Skills in Second Grade’. NeuroImage 82 (November): 605–15.CrossRefGoogle ScholarPubMed
Back, S. A., Riddle, A., and McClure, M. M.. 2007. ‘Maturation-Dependent Vulnerability of Perinatal White Matter in Premature Birth’. Stroke: A Journal of Cerebral Circulation 38 (2 Suppl): 724–30.CrossRefGoogle ScholarPubMed
Badawi, N., Kurinczuk, J. J., Keogh, J. M., et al. 1998. ‘Antepartum Risk Factors for Newborn Encephalopathy: The Western Australian Case-Control Study’. BMJ 317 (7172): 1549–53.Google ScholarPubMed
Bajic, D., Commons, K. G., and Soriano, S. G.. 2013. ‘Morphine-Enhanced Apoptosis in Selective Brain Regions of Neonatal Rats’. International Journal of Developmental Neuroscience: The Official Journal of the International Society for Developmental Neuroscience 31 (4): 258–66.CrossRefGoogle ScholarPubMed
Baker, L., and Wigfield, A.. 1999. ‘Dimensions of Children’s Motivation for Reading and Their Relations to Reading Activity and Reading Achievement’. Reading Research Quarterly 34 (4): 452–77.CrossRefGoogle Scholar
Ballard, O., and Morrow, A. L.. 2013. ‘Human Milk Composition: Nutrients and Bioactive Factors’. Pediatric Clinics of North America 60 (1): 49–74.CrossRefGoogle ScholarPubMed
Bander, R. S., and Betz, N. E.. 1981. ‘The Relationship of Sex and Sex Role to Trait and Situationally Specific Anxiety Types’. Journal of Research in Personality 15 (3): 312–22.CrossRefGoogle Scholar
Banfi, C., Kemény, F., Gangl, M., et al. 2018. ‘Visual Attention Span Performance in German-Speaking Children with Differential Reading and Spelling Profiles: No Evidence of Group Differences’. PloS One 13 (6): e0198903.CrossRefGoogle ScholarPubMed
Bar, S., Milanaik, R., and Adesman, A.. 2016. ‘Long-Term Neurodevelopmental Benefits of Breastfeeding’. Current Opinion in Pediatrics 28 (4): 559–66.CrossRefGoogle ScholarPubMed
Barbosa, F., Jr, Tanus-Santos, J. E., Gerlach, R. F., and Parsons, P. J.. 2005. ‘A Critical Review of Biomarkers Used for Monitoring Human Exposure to Lead: Advantages, Limitations, and Future Needs’. Environmental Health Perspectives 113 (12): 1669–74.CrossRefGoogle ScholarPubMed
Bardach, E. 1974. The Implementation Game. MIT Press.Google Scholar
Bardach, E. 1978. The Implementation Game. MIT Press. https://mitpress.mit.edu/books/implementation-game.Google Scholar
Bar-Kochva, I., and Amiel, M.. 2016. ‘The Relations between Reading and Spelling: An Examination of Subtypes of Reading Disability’. Annals of Dyslexia 66 (2): 219–34.CrossRefGoogle ScholarPubMed
Barquero, L. A., Davis, N., and Cutting, L. E.. 2014. ‘Neuroimaging of Reading Intervention: A Systematic Review and Activation Likelihood Estimate Meta-Analysis’. PloS One 9 (1): e83668.CrossRefGoogle ScholarPubMed
Barres, B. A., and Raff, M. C. C.. 1993. ‘Proliferation of Oligodendrocyte Precursor Cells Depends on Electrical Activity in Axons’. Nature 361 (21): 258–60.CrossRefGoogle ScholarPubMed
Barroso, C., Ganley, C. M., McGraw, A. L., et al. 2020. ‘A Meta-Analysis of the Relation between Math Anxiety and Math Achievement’. Psychological Bulletin, 147 (2): 134–68. https://doi.org/10.1037/bul0000307.Google ScholarPubMed
Barrouillet, P., Mignon, M., and Thevenot, C.. 2008. ‘Strategies in Subtraction Problem Solving in Children’. Journal of Experimental Child Psychology 99 (4): 233–51.CrossRefGoogle ScholarPubMed
Basten, M., Jaekel, J., Johnson, S., Gilmore, C., and Wolke, D.. 2015. ‘Preterm Birth and Adult Wealth: Mathematics Skills Count’. Psychological Science 26 (10): 1608–19.CrossRefGoogle ScholarPubMed
Batista-García-Ramó, Karla, and Fernández-Verdecia, Caridad Ivette. 2018. ‘What We Know About the Brain Structure-Function Relationship’. Behavioral Sciences 8 (4). https://doi.org/10.3390/bs8040039.CrossRefGoogle ScholarPubMed
Bauer, A.-K. R., Debener, S., and Nobre, A. C.. 2020. ‘Synchronisation of Neural Oscillations and Cross-Modal Influences’. Trends in Cognitive Sciences 24 (6): 481–95.CrossRefGoogle ScholarPubMed
Beaulieu, C., Plewes, C., Paulson, L. A., et al. 2005. ‘Imaging Brain Connectivity in Children with Diverse Reading Ability’. NeuroImage 25 (4): 1266–71.CrossRefGoogle ScholarPubMed
Beilock, S. L. 2008. ‘Math Performance in Stressful Situations’. Current Directions in Psychological Science 17 (5): 339–43.CrossRefGoogle Scholar
Beilock, S. L., Gunderson, E. A., Ramirez, G., and Levine, S. C.. 2010. ‘Female Teachers’ Math Anxiety Affects Girls’ Math Achievement’. Proceedings of the National Academy of Sciences of the United States of America 107 (5): 1860–63.Google ScholarPubMed
Bellato, A., Arora, I., Hollis, C., and Groom, M. J.. 2020. ‘Is Autonomic Nervous System Function Atypical in Attention Deficit Hyperactivity Disorder (ADHD)? A Systematic Review of the Evidence’. Neuroscience and Biobehavioral Reviews 108 (January): 182–206.CrossRefGoogle ScholarPubMed
Bellinger, D. C., O’Leary, K, Rainis, H., and Gibb, H. J.. 2016. ‘Country-Specific Estimates of the Incidence of Intellectual Disability Associated with Prenatal Exposure to Methylmercury’. Environmental Research 147 (May): 159–63.CrossRefGoogle ScholarPubMed
Beltrán-Campos, V., Silva-Vera, M., García-Campos, M. L., and Díaz-Cintra, S.. 2015. ‘Effects of Morphine on Brain Plasticity’. Neurología (English Edition) 30 (3): 176–80.CrossRefGoogle ScholarPubMed
Ben-Shachar, M., Dougherty, R. F., Deutsch, G. K., and Wandell, B. A.. 2011. ‘The Development of Cortical Sensitivity to Visual Word Forms’. Journal of Cognitive Neuroscience 23 (9): 2387–99.CrossRefGoogle ScholarPubMed
Ben-Shachar, M., Dougherty, R. F., and Wandell, B. A.. 2007. ‘White Matter Pathways in Reading’. Current Opinion in Neurobiology 17 (2): 258–70.CrossRefGoogle ScholarPubMed
Bentley, J. P., Roberts, C. L., Bowen, J. R., et al. 2016. ‘Planned Birth Before 39 Weeks and Child Development: A Population-Based Study’. Pediatrics 138 (6). https://doi.org/10.1542/peds.2016-2002.CrossRefGoogle ScholarPubMed
Berghuis, P., Dobszay, M. B., Wang, X., et al. 2005. ‘Endocannabinoids Regulate Interneuron Migration and Morphogenesis by Transactivating the TrkB Receptor’. Proceedings of the National Academy of Sciences of the United States of America 102 (52): 19115–20.Google ScholarPubMed
Berglundh, S., Vollrath, M., Brantsæter, A. L., et al. 2021. ‘Maternal Caffeine Intake during Pregnancy and Child Neurodevelopment up to Eight Years of Age: Results from the Norwegian Mother, Father and Child Cohort Study’. European Journal of Nutrition 60 (2): 791–805.CrossRefGoogle ScholarPubMed
Berman, P. and McLaughlin, M. W.. 1976. ‘Implementation of Educational Innovation’. The Educational Forum 40 (3): 345–70.CrossRefGoogle Scholar
Bernard-Bonnin, A. C., Canadian Paediatric Society, Mental Health and Developmental Disabilities Committee. ‘Maternal Depression and Child Development’. 2004. Paediatrics & Child Health 9 (8): 575–83.Google Scholar
Berteletti, I., Prado, J., and Booth, J. R.. 2014. ‘Children with Mathematical Learning Disability Fail in Recruiting Verbal and Numerical Brain Regions When Solving Simple Multiplication Problems’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 57 (August): 143–55.CrossRefGoogle ScholarPubMed
Betz, N. E. 1978. ‘Prevalence, Distribution, and Correlates of Math Anxiety in College Students’. Journal of Counseling Psychology 25 (5): 441–48.CrossRefGoogle Scholar
Bhide, A., Power, A., and Goswami, U.. 2013. ‘A Rhythmic Musical Intervention for Poor Readers: A Comparison of Efficacy with a Letter-Based Intervention’. Mind, Brain and Education: The Official Journal of the International Mind, Brain, and Education Society 7 (2): 113–23.CrossRefGoogle Scholar
Bieg, M., Goetz, T., and Lipnevich, A. A.. 2014. ‘What Students Think They Feel Differs from What They Really Feel: Academic Self-Concept Moderates the Discrepancy between Students’ Trait and State Emotional Self-Reports’. PloS One 9 (3): e92563.CrossRefGoogle ScholarPubMed
‘Biomonitoring Summary’. 2019a. May 6, 2019. www.cdc.gov/biomonitoring/Benzene_BiomonitoringSummary.html.Google Scholar
‘Biomonitoring Summary’. 2019b. May 6, 2019. www.cdc.gov/biomonitoring/Benzene_BiomonitoringSummary.html.Google Scholar
Bishop, D. V., and Adams, C.. 1990. ‘A Prospective Study of the Relationship between Specific Language Impairment, Phonological Disorders and Reading Retardation’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 31 (7): 1027–50.Google ScholarPubMed
Black, J. M., Xia, Z., and Hoeft, F.. 2017. ‘Neurobiological Bases of Reading Disorder Part II: The Importance of Developmental Considerations in Typical and Atypical Reading’. Language and Linguistics Compass 11 (10): 1–26.CrossRefGoogle ScholarPubMed
Blau, V., Reithler, J., van Atteveldt, N., et al. 2010. ‘Deviant Processing of Letters and Speech Sounds as Proximate Cause of Reading Failure: A Functional Magnetic Resonance Imaging Study of Dyslexic Children’. Brain: A Journal of Neurology 133 (Pt 3): 868–79.CrossRefGoogle ScholarPubMed
Bleker, L. S., de Rooij, S. R., and Roseboom, T. J.. 2019. ‘Prenatal Psychological Stress Exposure and Neurodevelopment and Health of Children’. International Journal of Environmental Research and Public Health 16 (19): 3657. https://doi.org/10.3390/ijerph16193657.CrossRefGoogle ScholarPubMed
Blencowe, H., Cousens, S, Oestergaard, M. Z., et al. 2012. ‘National, Regional, and Worldwide Estimates of Preterm Birth Rates in the Year 2010 with Time Trends since 1990 for Selected Countries: A Systematic Analysis and Implications’. The Lancet 379 (9832): 2162–72.CrossRefGoogle ScholarPubMed
Bloechle, J., Huber, S., Bahnmueller, J., et al. 2016. ‘Fact Learning in Complex Arithmetic-the Role of the Angular Gyrus Revisited’. Human Brain Mapping 37 (9): 3061–79.CrossRefGoogle ScholarPubMed
Boets, B., and De Smedt, B.. 2010. ‘Single-Digit Arithmetic in Children with Dyslexia’. Dyslexia 16 (2): 183–91.CrossRefGoogle ScholarPubMed
Boets, B., Op de Beeck, H. P, Vandermosten, M., et al. 2013. ‘Intact but Less Accessible Phonetic Representations in Adults with Dyslexia’. Science 342 (6163): 1251–4.CrossRefGoogle ScholarPubMed
Boets, B., Vandermosten, M., Poelmans, H., et al. 2011. ‘Preschool Impairments in Auditory Processing and Speech Perception Uniquely Predict Future Reading Problems’. Research in Developmental Disabilities 32 (2): 560–70.CrossRefGoogle ScholarPubMed
Borchers, L R., Bruckert, L, Dodson, C. K., et al. 2019. ‘Microstructural Properties of White Matter Pathways in Relation to Subsequent Reading Abilities in Children: A Longitudinal Analysis’. Brain Structure & Function 224 (2): 891–905.CrossRefGoogle ScholarPubMed
Bortolato, M., Bini, V., Frau, R., et al. 2014. ‘Juvenile Cannabinoid Treatment Induces Frontostriatal Gliogenesis in Lewis Rats’. European Neuropsychopharmacology: The Journal of the European College of Neuropsychopharmacology 24 (6): 974–85.CrossRefGoogle ScholarPubMed
Bosse, M.-L., Tainturier, M. J., and Valdois, S.. 2007. ‘Developmental Dyslexia: The Visual Attention Span Deficit Hypothesis’. Cognition 104 (2): 198–230.CrossRefGoogle ScholarPubMed
Bosse, M.-L., and Valdois, S.. 2009. ‘Influence of the Visual Attention Span on Child Reading Performance: A Cross-Sectional Study’. Journal of Research in Reading 32 (2): 230–53.CrossRefGoogle Scholar
Boucher, O., Muckle, G, Jacobson, J. L., et al. 2014. ‘Domain-Specific Effects of Prenatal Exposure to PCBs, Mercury, and Lead on Infant Cognition: Results from the Environmental Contaminants and Child Development Study in Nunavik’. Environmental Health Perspectives 122 (3): 310–16.CrossRefGoogle ScholarPubMed
Boulet-Craig, A., Robaey, P., Lacourse, K., et al. 2017. ‘Visual Short Term Memory Related Brain Activity Predicts Mathematical Abilities’. Neuropsychology 31 (5): 535–45.CrossRefGoogle ScholarPubMed
Bowman, C. R., and Zeithamova, D.. 2018. ‘Abstract Memory Representations in the Ventromedial Prefrontal Cortex and Hippocampus Support Concept Generalization’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 38 (10): 2605–14.CrossRefGoogle ScholarPubMed
Brady, S. A., Braze, D., and Fowler, C. A.. 2011. Explaining Individual Differences in Reading: Theory and Evidence. Psychology Press.CrossRefGoogle Scholar
Brain Development Cooperative Group. 2012. ‘Total and Regional Brain Volumes in a Population-Based Normative Sample from 4 to 18 Years: The NIH MRI Study of Normal Brain Development’. Cerebral Cortex 22 (1): 1–12.CrossRefGoogle Scholar
Braun, J. M., Kahn, R. S., Froehlich, T., Auinger, P., and Lanphear, B. P.. 2006. ‘Exposures to Environmental Toxicants and Attention Deficit Hyperactivity Disorder in US Children’. Environmental Health Perspectives 114 (12): 1904–9.CrossRefGoogle Scholar
Brem, S., Bach, S., Kucian, K, et al. 2010. ‘Brain Sensitivity to Print Emerges When Children Learn Letter-Speech Sound Correspondences’. Proceedings of the National Academy of Sciences of the United States of America 107 (17): 7939–44.Google ScholarPubMed
Brem, S., Halder, P., Bucher, K., et al. 2009. ‘Tuning of the Visual Word Processing System: Distinct Developmental ERP and fMRI Effects’. Human Brain Mapping 30 (6): 1833–44.CrossRefGoogle ScholarPubMed
Brem, S., Maurer, U., Kronbichler, M., et al. 2020. ‘Visual Word Form Processing Deficits Driven by Severity of Reading Impairments in Children with Developmental Dyslexia’. Scientific Reports 10 (1): 18728.CrossRefGoogle ScholarPubMed
Brennan, A. R., and Arnsten, A. F. T.. 2008. ‘Neuronal Mechanisms Underlying Attention Deficit Hyperactivity Disorder: The Influence of Arousal on Prefrontal Cortical Function’. Annals of the New York Academy of Sciences 1129: 236–45.CrossRefGoogle ScholarPubMed
Bressler, J. P., and Goldstein, G. W.. 1991. ‘Mechanisms of Lead Neurotoxicity’. Biochemical Pharmacology 41 (4): 479–84.CrossRefGoogle ScholarPubMed
‘Brominated Flame Retardants’. n.d. Accessed July 21, 2021. www.efsa.europa.eu/en/topics/topic/brominated-flame-retardants.Google Scholar
Brossard-Racine, M., du Plessis, A. J., and Limperopoulos, C.. 2015. ‘Developmental Cerebellar Cognitive Affective Syndrome in Ex-Preterm Survivors Following Cerebellar Injury’. Cerebellum 14 (2): 151–64.CrossRefGoogle ScholarPubMed
Browning, R., Marshall, D., and Tabb, D.. 1981. ‘Implementation and Political Change: Sources of Local Variation in Federal Social Programs’. In Effective Policy Implementation, edited by D. Mazmanian and P. Sabatier. D. C. Heath.Google Scholar
Brubaker, C. J., Dietrich, K. N., Lanphear, B. P., and Cecil, K. M.. 2010. ‘The Influence of Age of Lead Exposure on Adult Gray Matter Volume’. Neurotoxicology 31 (3): 259–66.CrossRefGoogle ScholarPubMed
Brubaker, C. J., Schmithorst, V. J., Haynes, E. N., et al. 2009. ‘Altered Myelination and Axonal Integrity in Adults with Childhood Lead Exposure: A Diffusion Tensor Imaging Study’. Neurotoxicology 30 (6): 867–75.CrossRefGoogle ScholarPubMed
Bruckert, L., Borchers, L. R., Dodson, C. K., et al. 2019. ‘White Matter Plasticity in Reading-Related Pathways Differs in Children Born Preterm and at Term: A Longitudinal Analysis’. Frontiers in Human Neuroscience 13 (May): 139.CrossRefGoogle ScholarPubMed
Bublitz, M. H., and Stroud, L. R.. 2012. ‘Maternal Smoking during Pregnancy and Offspring Brain Structure and Function: Review and Agenda for Future Research’. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco 14 (4): 388–97.CrossRefGoogle ScholarPubMed
Bugden, S., and Ansari, D.. 2016. ‘Probing the Nature of Deficits in the “Approximate Number System” in Children with Persistent Developmental Dyscalculia’. Developmental Science 19 (5): 817–33. https://doi.org/10.1111/desc.12324.CrossRefGoogle ScholarPubMed
Bulik-Sullivan, B., Finucane, H. K., Anttila, V., et al. 2015. ‘An Atlas of Genetic Correlations across Human Diseases and Traits’. Nature Genetics 47 (11): 1236–41.CrossRefGoogle ScholarPubMed
Bullock, T. H., Bennett, M. V. L., Johnston, D., et al. 2005. ‘The Neuron Doctrine, Redux’. Science 310 (5749): 791–93.CrossRefGoogle ScholarPubMed
Bulthé, J., Prinsen, J., Vanderauwera, J., et al. 2019. ‘Multi-Method Brain Imaging Reveals Impaired Representations of Number as Well as Altered Connectivity in Adults with Dyscalculia’. NeuroImage 190: 289–302. https://doi.org/10.1016/j.neuroimage.2018.06.012.CrossRefGoogle ScholarPubMed
Burbacher, T. M., Rodier, P. M., and Weiss, B.. 1990. ‘Methylmercury Developmental Neurotoxicity: A Comparison of Effects in Humans and Animals’. Neurotoxicology and Teratology 12 (3): 191–202.CrossRefGoogle ScholarPubMed
Burr, D., and Ross, J.. 2008. ‘A Visual Sense of Number’. Current Biology: CB 18 (6): 425–28.CrossRefGoogle ScholarPubMed
Butterworth, Brian. 2011. ‘Chapter 16 – Foundational Numerical Capacities and the Origins of Dyscalculia**Reprinted from Trends in Cognitive Sciences, Vol 14, Brian Butterworth, Foundational Numerical Capacities and the Origins of Dyscalculia, Pg 534–541, 2010, with Permission from Elsevier.’ In Space, Time and Number in the Brain, edited by Dehaene, S. and Brannon, E. M., 249–65. Academic Press.Google Scholar
Butterworth, Brian, and Walsh, Vincent. 2011. ‘Neural Basis of Mathematical Cognition’. Current Biology 21 (16): PR618–R621. https://doi.org/10.1016/j.cub.2011.07.005.CrossRefGoogle ScholarPubMed
Butterworth, B., Varma, S., and Laurillard, D.. 2011. ‘Dyscalculia: From Brain to Education’. Science, 27, 1049–53. https://doi.org/10.1126/science.1201536.Google Scholar
Buzsáki, G., and Wang, X. J.. 2012. ‘Mechanisms of Gamma Oscillations’. Annu Rev Neurosci. 35: 203–25. doi: 10.1146/annurev-neuro-062111-150444.CrossRefGoogle Scholar
Cabrera, O. H., O’Connor, S. D., Swiney, B. S., et al. 2017. ‘Caffeine Combined with Sedative/Anesthetic Drugs Triggers Widespread Neuroapoptosis in a Mouse Model of Prematurity’. The Journal of Maternal-Fetal & Neonatal Medicine: The Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians 30 (22): 2734–41.CrossRefGoogle Scholar
Cai, K., Song, Q., Yuan, W., et al. 2020. ‘Human Exposure to PBDEs in E-Waste Areas: A Review’. Environmental Pollution 267 (December): 115634.CrossRefGoogle ScholarPubMed
Cannizzaro, C., Plescia, F., Martire, M., et al. 2006. ‘Single, Intense Prenatal Stress Decreases Emotionality and Enhances Learning Performance in the Adolescent Rat Offspring: Interaction with a Brief, Daily Maternal Separation’. Behavioural Brain Research 169 (1): 128–36.CrossRefGoogle ScholarPubMed
Cantlon, J. F., Brannon, E. M., Carter, E. J., and Pelphrey, K. A.. 2006. ‘Functional Imaging of Numerical Processing in Adults and 4-y-Old Children’. PLoS Biology 4 (5): e125.CrossRefGoogle ScholarPubMed
Cantlon, J. F., and Li., R. 2013. ‘Neural Activity During Natural Viewing of Sesame Street Statistically Predicts Test Scores in Early Childhood’. PLoS Biology 11 (1): e1001462.CrossRefGoogle ScholarPubMed
Cappelletti, M., Didino, D., Stoianov, I., and Zorzi, M.. 2014. ‘Number Skills Are Maintained in Healthy Ageing’. Cognitive Psychology 69 (March): 25–45.CrossRefGoogle ScholarPubMed
Carey, E., Devine, A., Hill, F., et al. 2019. ‘Understanding Mathematics Anxiety: Investigating the Experiences of UK Primary and Secondary School Students’. Apollo – University of Cambridge Repository. https://doi.org/10.17863/CAM.37744.CrossRefGoogle Scholar
Carey, E., Devine, A., Hill, F., and Szűcs, D.. 2017. ‘Differentiating Anxiety Forms and Their Role in Academic Performance from Primary to Secondary School’. PloS One 12 (3): e0174418.CrossRefGoogle ScholarPubMed
Carey, E., Hill, F., Devine, A., and Szücs, D.. 2015. ‘The Chicken or the Egg? The Direction of the Relationship between Mathematics Anxiety and Mathematics Performance’. Frontiers in Psychology 6: 1987.Google ScholarPubMed
Carey, E., Hill, F., Devine, A., and Szűcs, D.. 2017. ‘The Modified Abbreviated Math Anxiety Scale: A Valid and Reliable Instrument for Use with Children’. Frontiers in Psychology 8 (January): 11.CrossRefGoogle Scholar
Carrillo-Reid, L., Yang, W., Bando, Y., Peterka, D. S., and Yuste, R.. 2016. ‘Imprinting and Recalling Cortical Ensembles’. Science 353 (6300): 691–4.CrossRefGoogle ScholarPubMed
Casad, B. J., Hale, P., and Wachs, F. L.. 2015. ‘Parent-Child Math Anxiety and Math-Gender Stereotypes Predict Adolescents’ Math Education Outcomes’. Frontiers in Psychology 6 (November): 1597.CrossRefGoogle ScholarPubMed
Cascio, C. J., Gerig, G., and Piven, J.. 2007. ‘Diffusion Tensor Imaging: Application to the Study of the Developing Brain’. Journal of the American Academy of Child and Adolescent Psychiatry 46 (2): 213–23.Google Scholar
Casey, R., Levy, S. E., Brown, K., and Brooks-Gunn, J.. 1992. ‘Impaired Emotional Health in Children with Mild Reading Disability’. Journal of Developmental and Behavioral Pediatrics: JDBP 13 (4): 256–60.CrossRefGoogle ScholarPubMed
Caspi, A., Williams, B., Kim-Cohen, J, et al. 2007. ‘Moderation of Breastfeeding Effects on the IQ by Genetic Variation in Fatty Acid Metabolism’. Proceedings of the National Academy of Sciences of the United States of America 104 (47): 18860–65.Google ScholarPubMed
Castaldi, E., Piazza, M., and Iuculano, T.. 2020. ‘Learning Disabilities: Developmental Dyscalculia’. Handbook of Clinical Neurology 174: 61–75.CrossRefGoogle ScholarPubMed
Castles, A., and Coltheart, M.. 1993. ‘Varieties of Developmental Dyslexia’. Cognition 47 (2): 149–80.CrossRefGoogle ScholarPubMed
Castoldi, A. F., Coccini, T., and Manzo, L.. 2003. ‘Neurotoxic and Molecular Effects of Methylmercury in Humans’. Reviews on Environmental Health 18 (1): 19–31.CrossRefGoogle ScholarPubMed
Caviola, S., Colling, L. J., Mammarella, I. C., and Szűcs, D.. 2020. ‘Predictors of Mathematics in Primary School: Magnitude Comparison, Verbal and Spatial Working Memory Measures’. Developmental Science 23 (6): e12957.CrossRefGoogle ScholarPubMed
Caviola, S., Primi, C., Chiesi, F., and Mammarella, I. C.. 2017. ‘Psychometric Properties of the Abbreviated Math Anxiety Scale (AMAS) in Italian Primary School Children’. Learning and Individual Differences 55 (April): 174–82.CrossRefGoogle Scholar
Cecil, K. M., Brubaker, C. J., Adler, C. M., et al. 2008. ‘Decreased Brain Volume in Adults with Childhood Lead Exposure’. PLoS Medicine 5 (5): e112.CrossRefGoogle ScholarPubMed
Cecil, K. M., Dietrich, K. N., Mekibib Altaye, , et al. 2011. ‘Proton Magnetic Resonance Spectroscopy in Adults with Childhood Lead Exposure’. Environmental Health Perspectives 119 (3): 403–8.CrossRefGoogle ScholarPubMed
Centanni, T. M., Norton, E. S., Ozernov-Palchik, O., et al. 2019. ‘Disrupted Left Fusiform Response to Print in Beginning Kindergartners Is Associated with Subsequent Reading’. NeuroImage. Clinical 22 (November 2018): 101715.CrossRefGoogle ScholarPubMed
Center for Food Safety, and Applied Nutrition. 2020. ‘Advice about Eating Fish’. www.fda.gov/food/consumers/advice-about-eating-fish.Google Scholar
Cernerud, L., Eriksson, M., Jonsson, B., Steneroth, G., and Zetterström, R.. 1996. ‘Amphetamine Addiction during Pregnancy: 14-Year Follow-up of Growth and School Performance’. Acta Paediatrica 85 (2): 204–8.CrossRefGoogle ScholarPubMed
Chandramouli, K., Steer, C. D., Ellis, M., and Emond, A. M.. 2009. ‘Effects of Early Childhood Lead Exposure on Academic Performance and Behaviour of School Age Children’. Archives of Disease in Childhood 94 (11): 844–48.CrossRefGoogle ScholarPubMed
Chang, H., and Beilock, S. L.. 2016. ‘The Math Anxiety-Math Performance Link and Its Relation to Individual and Environmental Factors: A Review of Current Behavioral and Psychophysiological Research’. Current Opinion in Behavioral Sciences 10 (August): 33–38.CrossRefGoogle Scholar
Chang, H., Rosenberg-Lee, M., Qin, S., and Menon, V.. 2019. ‘Faster Learners Transfer Their Knowledge Better: Behavioral, Mnemonic, and Neural Mechanisms of Individual Differences in Children’s Learning’. Developmental Cognitive Neuroscience 40 (December): 100719.CrossRefGoogle ScholarPubMed
Chang, S., Chen, C, Yang, Z, and David Rodrigues, A.. 2009. ‘Further Assessment of 17alpha-Ethinyl Estradiol as an Inhibitor of Different Human Cytochrome P450 Forms in Vitro’. Drug Metabolism and Disposition: The Biological Fate of Chemicals 37 (8): 1667–75.CrossRefGoogle ScholarPubMed
Chang, T.Arron, -T Metcalfe, W. S., Padmanabhan, A, Chen, T, and Menon, V. 2016. ‘Heterogeneous and Nonlinear Development of Human Posterior Parietal Cortex Function’. NeuroImage 126 (February): 184–95.CrossRefGoogle ScholarPubMed
Charleston, J. S., Body, R. L., Bolender, R. P., et al. 1996. ‘Changes in the Number of Astrocytes and Microglia in the Thalamus of the Monkey Macaca Fascicularis Following Long-Term Subclinical Methylmercury Exposure’. Neurotoxicology 17 (1): 127–38.Google ScholarPubMed
Chen, A., Yolton, K, Rauch, S. A., et al. 2014. ‘Prenatal Polybrominated Diphenyl Ether Exposures and Neurodevelopment in US Children through 5 Years of Age: The HOME Study’. Environmental Health Perspectives 122 (8): 856–62.CrossRefGoogle ScholarPubMed
Chen, C. L., Wu, T. H., Cheng, M. C., et al. 2006. ‘Prospective Demonstration of Brain Plasticity after Intensive Abacus-Based Mental Calculation Training: An fMRI Study’. Nuclear Instruments & Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment 569 (2): 567–71.CrossRefGoogle Scholar
Cheng, D., Xiao, Q., Chen, Q, Cui, J, and Zhou, X. 2018. ‘Dyslexia and Dyscalculia Are Characterized by Common Visual Perception Deficits’. Developmental Neuropsychology 43 (6): 497–507.CrossRefGoogle ScholarPubMed
Chen, N. T., Zheng, M, and Suk-Han Ho, C. 2019. ‘Examining the Visual Attention Span Deficit Hypothesis in Chinese Developmental Dyslexia’. Reading and Writing 32 (3): 639–62.CrossRefGoogle Scholar
Chen, S., Zhou, Z., Fang, M. and McClelland, J. L.. 2018. ‘Can Generic Neural Networks Estimate Numerosity Like Humans?’ Cognitive Science. https://stanford.edu/~jlmcc/papers/ChenZhouFangMcC18Estimation.pdfGoogle Scholar
Child, A. E., Cirino, P. T., Fletcher, J. M., Willcutt, E. G., and Fuchs, L. S.. 2019. ‘A Cognitive Dimensional Approach to Understanding Shared and Unique Contributions to Reading, Math, and Attention Skills’. Journal of Learning Disabilities 52 (1): 15–30.CrossRefGoogle ScholarPubMed
Choe, K. W., Jenifer, J. B., Rozek, C. S., Berman, M. G., and Beilock, S. L.. 2019. ‘Calculated Avoidance: Math Anxiety Predicts Math Avoidance in Effort-Based Decision-Making’. Science Advances 5 (11): eaay1062.CrossRefGoogle ScholarPubMed
Cho, K., Frijters, J. C., Zhang, H, Miller, L. L., and Gruen, J. R.. 2013. ‘Prenatal Exposure to Nicotine and Impaired Reading Performance’. The Journal of Pediatrics 162 (4): 713–18.CrossRefGoogle ScholarPubMed
Cho, S., Metcalfe, A. W. S., Young, C. B., et al. 2012. ‘Hippocampal-Prefrontal Engagement and Dynamic Causal Interactions in the Maturation of Children’s Fact Retrieval’. Journal of Cognitive Neuroscience 24 (9): 1849–66.CrossRefGoogle ScholarPubMed
Chung, K. K. H., McBride-Chang, C, Wong, S. W. L., et al. 2008. ‘The Role of Visual and Auditory Temporal Processing for Chinese Children with Developmental Dyslexia’. Annals of Dyslexia 58 (1): 15–35.CrossRefGoogle ScholarPubMed
Chyl, K., Fraga-González, G, Brem, S, and Jednoróg, K.. 2021. ‘Brain Dynamics of (a)Typical Reading Development-a Review of Longitudinal Studies’. NPJ Science of Learning 6 (1): 4.CrossRefGoogle ScholarPubMed
Chyl, K., Kossowski, B, Dębska, A, et al. 2019. ‘Reading Acquisition in Children: Developmental Processes and Dyslexia-Specific Effects’. Journal of the American Academy of Child and Adolescent Psychiatry 58 (10): 948–60.Google ScholarPubMed
Cicchini, G. M., Anobile, G, and Burr, D. C.. 2016. ‘Spontaneous Perception of Numerosity in Humans’. Nature Communications 7 (August): 12536.Google Scholar
Cicero, T. J., Ellis, M. S., and Kasper, Z. A.. 2020. ‘Polysubstance Use: A Broader Understanding of Substance Use During the Opioid Crisis’. American Journal of Public Health 110 (2): 244–50.CrossRefGoogle ScholarPubMed
Cipolotti, L., Butterworth, B, and Denes, G. 1991. ‘A Specific Deficit For Numbers In A Case Of Dense Acalculia’. Brain 114 (6): 2619–37. https://doi.org/10.1093/brain/114.6.2619.CrossRefGoogle Scholar
Cipora, K., Szczygieł, M, Willmes, K, and Nuerk, H.-C. 2015. ‘Math Anxiety Assessment with the Abbreviated Math Anxiety Scale: Applicability and Usefulness: Insights from the Polish Adaptation’. Frontiers in Psychology 6 (November): 1833.CrossRefGoogle ScholarPubMed
Cirino, P. T., Fuchs, L. S., Elias, J. T., Powell, S. R., and Schumacher, R. F.. 2015. ‘Cognitive and Mathematical Profiles for Different Forms of Learning Difficulties’. Journal of Learning Disabilities 48 (2): 156–75.CrossRefGoogle ScholarPubMed
Clark, K. A., Helland, T, Specht, K, et al. 2014. ‘Neuroanatomical Precursors of Dyslexia Identified from Pre-Reading through to Age 11’. Brain: A Journal of Neurology 137 (Pt 12): 3136–41.CrossRefGoogle ScholarPubMed
Cleveland, L. M., Minter, M. L., Cobb, K. A., Scott, A. A., and German, V. F.. 2008. ‘Lead Hazards for Pregnant Women and Children: Part 1: Immigrants and the Poor Shoulder Most of the Burden of Lead Exposure in This Country. Part 1 of a Two-Part Article Details How Exposure Happens, Whom It Affects, and the Harm It Can Do’. The American Journal of Nursing 108 (10): 40–49; quiz 50.Google ScholarPubMed
Cohen, J. T., Bellinger, D. C., Connor, W. E., et al. 2005. ‘A Quantitative Risk-Benefit Analysis of Changes in Population Fish Consumption’. American Journal of Preventive Medicine 29 (4): 325–34.CrossRefGoogle ScholarPubMed
Cohen Kadosh, R., Kadosh, K. C., Kaas, A, Henik, A, and Goebel, R. 2007. ‘Notation-Dependent and -Independent Representations of Numbers in the Parietal Lobes’. Neuron 53 (2): 307–14.CrossRefGoogle ScholarPubMed
Coles, C. D., Platzman, K. A., Raskind-Hood, C. L., et al. 1997. ‘A Comparison of Children Affected by Prenatal Alcohol Exposure and Attention Deficit, Hyperactivity Disorder’. Alcoholism, Clinical and Experimental Research 21 (1): 150–61.CrossRefGoogle ScholarPubMed
Collet, G., Colin, C., Serniclaes, W., et al. 2012. ‘Effect of Phonological Training in French Children with SLI: Perspectives on Voicing Identification, Discrimination and Categorical Perception’. Research in Developmental Disabilities 33 (6): 1805–18.CrossRefGoogle ScholarPubMed
Collin, S. H. P., Milivojevic, B, and Doeller, C. F.. 2015. ‘Memory Hierarchies Map onto the Hippocampal Long Axis in Humans’. Nature Neuroscience 18 (11): 1562–64.CrossRefGoogle ScholarPubMed
Coltheart, M. 1978. ‘Lexical Access in Simple Reading Tasks’. Strategies of Information Processing, 151–216.Google Scholar
Coltheart, M., Rastle, K., Perry, C., Langdon, R., and Ziegler, J.. 2001. ‘DRC: A Dual Route Cascaded Model of Visual Word Recognition and Reading Aloud’. Psychological Review 108 (1): 204–56.Google Scholar
Conley, D., Rauscher, E, Dawes, C, Magnusson, P. K.E., and Siegal, M. L.. 2013. ‘Heritability and the Equal Environments Assumption: Evidence from Multiple Samples of Misclassified Twins’. Behavior Genetics 43 (5): 415–26.CrossRefGoogle ScholarPubMed
Conradt, E., Flannery, T, Aschner, J. L., et al. 2019. ‘Prenatal Opioid Exposure: Neurodevelopmental Consequences and Future Research Priorities’. Pediatrics 144 (3). https://doi.org/10.1542/peds.2019-0128.CrossRefGoogle ScholarPubMed
Constantinidis, C., and Klingberg, T.. 2016. ‘The Neuroscience of Working Memory Capacity and Training’. Nature Reviews Neuroscience 17: 438–49. https://doi.org/10.1038/nrn.2016.43.CrossRefGoogle ScholarPubMed
Cope, N., Eicher, J. D., Meng, H, et al. 2012. ‘Variants in the DYX2 Locus Are Associated with Altered Brain Activation in Reading-Related Brain Regions in Subjects with Reading Disability’. NeuroImage 63 (1): 148–56. https://doi.org/10.1016/j.neuroimage.2012.06.037.CrossRefGoogle ScholarPubMed
Cornelissen, P., Richardson, A., Mason, A., Fowler, S., and Stein, J.. 1995. ‘Contrast Sensitivity and Coherent Motion Detection Measured at Photopic Luminance Levels in Dyslexics and Controls’. Vision Research 35 (10): 1483–94.CrossRefGoogle ScholarPubMed
Corriveau, K., Pasquini, E, and Goswami, U. 2007. ‘Basic Auditory Processing Skills and Specific Language Impairment: A New Look at an Old Hypothesis’. Journal of Speech, Language, and Hearing Research: JSLHR 50 (3): 647–66.CrossRefGoogle Scholar
Corsi, D. J., Hsu, H, Fell, D. B., Wen, S. W, and Walker, M. 2020. ‘Association of Maternal Opioid Use in Pregnancy With Adverse Perinatal Outcomes in Ontario, Canada, From 2012 to 2018’. JAMA Network Open 3 (7): e208256.CrossRefGoogle ScholarPubMed
Costa, L. G., and Giordano, G.. 2014. ‘Polybrominated Diphenyl Ethers’. In Encyclopedia of Toxicology (3rd ed.), edited by Wexler, P., 1032–4. Academic Press.Google Scholar
Costa, L. G., de Laat, R, Tagliaferri, S, and Pellacani, C. 2014. ‘A Mechanistic View of Polybrominated Diphenyl Ether (PBDE) Developmental Neurotoxicity’. Toxicology Letters 230 (2): 282–94.CrossRefGoogle ScholarPubMed
Cragg, L. and Gilmore, C. 2014. ‘Skills Underlying Mathematics: The Role of Executive Function in the Development of Mathematics Proficiency’. Trends in Neuroscience and Education 3 (2): 63–8.CrossRefGoogle Scholar
Crocker, N.,Riley, E. P., and Mattson, S. N.. 2015. ‘Visual-Spatial Abilities Relate to Mathematics Achievement in Children with Heavy Prenatal Alcohol Exposure’. Neuropsychology 29 (1): 108–16.CrossRefGoogle ScholarPubMed
Crump, K. S., Kjellström, T., Shipp, A. M., Silvers, A., and Stewart, A.. 1998. ‘Influence of Prenatal Mercury Exposure upon Scholastic and Psychological Test Performance: Benchmark Analysis of a New Zealand Cohort’. Risk Analysis: An Official Publication of the Society for Risk Analysis 18 (6): 701–13.CrossRefGoogle ScholarPubMed
Cumming, R., Wilson, A, and Goswami, U.. 2015. ‘Basic Auditory Processing and Sensitivity to Prosodic Structure in Children with Specific Language Impairments: A New Look at a Perceptual Hypothesis’. Frontiers in Psychology 6 (July): 972.CrossRefGoogle Scholar
Curran, E. A., O’Keeffe, G. W., Looney, A. M, et al. 2018. ‘Exposure to Hypertensive Disorders of Pregnancy Increases the Risk of Autism Spectrum Disorder in Affected Offspring’. Molecular Neurobiology 55 (7): 5557–64.CrossRefGoogle ScholarPubMed
Darki, F., Peyrard-Janvid, M, Matsson, H, Kere, J, and Klingberg, T. 2012. ‘Three Dyslexia Susceptibility Genes, DYX1C1, DCDC2, and KIAA0319, Affect Temporo-Parietal White Matter Structure’. Biological Psychiatry 72 (8): P671–6. https://doi.org/10.1016/j.biopsych.2012.05.008.CrossRefGoogle ScholarPubMed
Darki, F., Peyrard-Janvid, M, Matsson, H, Kere, J, and Klingberg, T 2014. ‘DCDC2 Polymorphism Is Associated with Left Temporoparietal Gray and White Matter Structures during Development’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 34 (43): 14455–62.CrossRefGoogle ScholarPubMed
Daskalakis, N. P., Bagot, R. C., Parker, K. J., Vinkers, C. H., and de Kloet, E. R.. 2013. ‘The Three-Hit Concept of Vulnerability and Resilience: Toward Understanding Adaptation to Early-Life Adversity Outcome’. Psychoneuroendocrinology 38 (9): 1858–73.CrossRefGoogle ScholarPubMed
Davidson, P. W., Leste, A, Benstrong, E, et al. 2010. ‘Fish Consumption, Mercury Exposure, and Their Associations with Scholastic Achievement in the Seychelles Child Development Study’. Neurotoxicology 31 (5): 439–47.CrossRefGoogle ScholarPubMed
Davis, C. J., Gayán, J., Knopik, V. S., et al. 2001. ‘Etiology of Reading Difficulties and Rapid Naming: The Colorado Twin Study of Reading Disability’. Behavior Genetics 31 (6): 625–35.CrossRefGoogle ScholarPubMed
Davis, N., Cannistraci, C. J., Rogers, B. P., et al. 2009. ‘Aberrant Functional Activation in School Age Children at-Risk for Mathematical Disability: A Functional Imaging Study of Simple Arithmetic Skill’. Neuropsychologia 47 (12): 2470–9. https://doi.org/10.1016/j.neuropsychologia.2009.04.024.CrossRefGoogle ScholarPubMed
Davis, O. S. P., Band, G, Pirinen, M., et al. 2014. ‘The Correlation between Reading and Mathematics Ability at Age Twelve Has a Substantial Genetic Component’. Nature Communications 5 (July): 4204.CrossRefGoogle Scholar
Day, N. L., Richardson, G. A., Goldschmidt, L., et al. 1994. ‘Effect of Prenatal Marijuana Exposure on the Cognitive Development of Offspring at Age Three’. Neurotoxicology and Teratology 16 (2): 169–75.CrossRefGoogle ScholarPubMed
Dean, J., Corrado, G. S., Monga, R, et al. 2012. ‘Large Scale Distributed Deep Networks’. http://research.google/pubs/pub40565/.Google Scholar
Dehaene-Lambertz, G., Monzalvo, K, and Dehaene, S. 2018. ‘The Emergence of the Visual Word Form: Longitudinal Evolution of Category-Specific Ventral Visual Areas during Reading Acquisition’. PLoS Biology 16 (3): e2004103.CrossRefGoogle ScholarPubMed
Dehaene, S., and Cohen, L.. 1997. ‘Cerebral Pathways for Calculation: Double Dissociation between Rote Verbal and Quantitative Knowledge of Arithmetic’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 33 (2): 219–50.CrossRefGoogle ScholarPubMed
Dehaene, S., and Cohen, L. 2011. ‘The Unique Role of the Visual Word Form Area in Reading’. Trends in Cognitive Sciences 15 (6): 254–62.CrossRefGoogle ScholarPubMed
Dehaene, S. 2001. ‘Precis of The Number Sense’. Mind and Language 16 (1): 16–36. https://doi.org/10.1111/1468-0017.00154.CrossRefGoogle Scholar
Dehaene, S 2011. The Number Sense: How the Mind Creates Mathematics, Revised and Updated Edition. Oxford University Press.Google Scholar
Dehaene, S., and Changeux, J.-P. 1993. ‘Development of Elementary Numerical Abilities: A Neuronal Model’. Journal of Cognitive Neuroscience 5 (4): 390–407. https://doi.org/10.1162/jocn.1993.5.4.390.CrossRefGoogle ScholarPubMed
Dehaene, S., Cohen, L, Morais, J, and Kolinsky, R. 2015. ‘Illiterate to Literate: Behavioural and Cerebral Changes Induced by Reading Acquisition’. Nature Reviews. Neuroscience 16 (4): 234–44.CrossRefGoogle ScholarPubMed
Dehaene, S., Piazza, M, Pinel, P, and Cohen, L. 2003. ‘Three Parietal Circuits for Number Processing’. Cognitive Neuropsychology 20 (3): 487–506.CrossRefGoogle ScholarPubMed
De La Cruz, V. M., Di Nuovo, A, Di Nuovo, S, and Cangelosi, A. 2014. ‘Making Fingers and Words Count in a Cognitive Robot’. Frontiers in Behavioral Neuroscience 8 (February): 13.Google Scholar
Delazer, M., Domahs, F, Lochy, A, et al. 2004. ‘Number Processing and Basal Ganglia Dysfunction: A Single Case Study’. Neuropsychologia 42 (8): 1050–62.CrossRefGoogle ScholarPubMed
Delazer, M., Domahs, F., Bartha, L., et al. 2003. ‘Learning Complex Arithmetic: An fMRI Study’. Brain Research. Cognitive Brain Research 18 (1): 76–88.CrossRefGoogle ScholarPubMed
Delazer, M., Ischebeck, A., Domahs, F., et al. 2005. ‘Learning by Strategies and Learning by Drill: Evidence from an fMRI Study’. NeuroImage 25 (3): 838–49.CrossRefGoogle ScholarPubMed
Demeyere, N., Rotshtein, P, and Humphreys, G. W.. 2012. ‘The Neuroanatomy of Visual Enumeration: Differentiating Necessary Neural Correlates for Subitizing versus Counting in a Neuropsychological Voxel-Based Morphometry Study’. Journal of Cognitive Neuroscience 24 (4): 948–64. https://doi.org/10.1162/jocn_a_00188.Google Scholar
Denes, G., Cipolotti, L, and Zorzi, M. 2020. ‘Acquired Dyslexias and Dysgraphias’. In Handbook of Clinical and Experimental Neuropsychology, 289–318. Psychology Press.CrossRefGoogle Scholar
Denes, G., and Pizzamiglio, L. 1999. Handbook of Clinical and Experimental Neuropsychology (1st ed.). Psychology Press. https://doi.org/10.4324/9781315791272CrossRefGoogle Scholar
Dennis, C.-L., Falah-Hassani, K, and Shiri, R. 2017. ‘Prevalence of Antenatal and Postnatal Anxiety: Systematic Review and Meta-Analysis’. The British Journal of Psychiatry: The Journal of Mental Science 210 (5): 315–23.CrossRefGoogle ScholarPubMed
Denny, C. H., Acero, C. S., Naimi, T. S., and Kim, S. Y.. 2019. ‘Consumption of Alcohol Beverages and Binge Drinking Among Pregnant Women Aged 18–44 Years – United States, 2015–2017’. MMWR. Morbidity and Mortality Weekly Report 68 (16): 365–8.CrossRefGoogle Scholar
Deoni, S., Dean, D 3rd, Joelson, S, O’Regan, J, and Schneider, N. 2018. ‘Early Nutrition Influences Developmental Myelination and Cognition in Infants and Young Children’. NeuroImage 178 (September): 649–59.CrossRefGoogle ScholarPubMed
Department for Education and Employment. 1999. The National Numeracy Strategy: Framework for Teaching Mathematics from Reception to Year 6. London: DfEE.Google Scholar
Der, G., Batty, G. D, and Deary, I. J.. 2006. ‘Effect of Breast Feeding on Intelligence in Children: Prospective Study, Sibling Pairs Analysis, and Meta-Analysis’. BMJ 333 (7575): 945.CrossRefGoogle ScholarPubMed
De Smedt, B., and Boets, B.. 2010. ‘Phonological Processing and Arithmetic Fact Retrieval: Evidence from Developmental Dyslexia’. Neuropsychologia 48 (14): 3973–81. doi: 10.1016/j.neuropsychologia.2010.10.018.Google Scholar
De Smedt, B., and Gilmore, C. K.. 2011. ‘Defective Number Module or Impaired Access? Numerical Magnitude Processing in First Graders with Mathematical Difficulties’. Journal of Experimental Child Psychology 108 (2): 278–92.CrossRefGoogle ScholarPubMed
De Smedt, B., Holloway, I. D., and Ansari, D. 2011. ‘Effects of Problem Size and Arithmetic Operation on Brain Activation during Calculation in Children with Varying Levels of Arithmetical Fluency’. NeuroImage 57 (3): 771–81.CrossRefGoogle ScholarPubMed
Deutsch, G. K., Dougherty, R. F., Bammer, R, et al. 2005. ‘Children’s Reading Performance Is Correlated with White Matter Structure Measured by Diffusion Tensor Imaging’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 41 (3): 354–63.CrossRefGoogle ScholarPubMed
Devine, A., Fawcett, K, Szűcs, D, and Dowker, A. 2012. ‘Gender Differences in Mathematics Anxiety and the Relation to Mathematics Performance While Controlling for Test Anxiety’. Behavioral and Brain Functions: BBF 8 (July): 33.CrossRefGoogle ScholarPubMed
Devine, A., Hill, F, Carey, E, and Szűcs, D. 2018. ‘Cognitive and Emotional Math Problems Largely Dissociate: Prevalence of Developmental Dyscalculia and Mathematics Anxiety’. Journal of Educational Psychology 110 (3): 431–44.CrossRefGoogle Scholar
De Visscher, A., and Noël, M.-P.. 2013. ‘A Case Study of Arithmetic Facts Dyscalculia Caused by a Hypersensitivity-to-Interference in Memory’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 49 (1): 50–70.CrossRefGoogle ScholarPubMed
De Vos, A., Vanvooren, S, Ghesquière, P, and Wouters, J. 2020. ‘Subcortical Auditory Neural Synchronization Is Deficient in Pre-Reading Children Who Develop Dyslexia’. Developmental Science 23 (6): e12945.CrossRefGoogle ScholarPubMed
De Vos, A., Vanvooren, S, Vanderauwera, J, Ghesquière, P, and Wouters, J. 2017a. ‘Atypical Neural Synchronization to Speech Envelope Modulations in Dyslexia’. Brain and Language 164 (January): 106–17.CrossRefGoogle ScholarPubMed
De Vos, A., Vanvooren, S, Vanderauwera, J, Ghesquière, P, and Wouters, J 2017b. ‘A Longitudinal Study Investigating Neural Processing of Speech Envelope Modulation Rates in Children with (a Family Risk For) Dyslexia’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 93 (August): 206–19.Google Scholar
Dew, K. H., and Galassi, J. P.. 1983. ‘Mathematics Anxiety: Some Basic Issues’. Journal of Counseling Psychology 30 (3): 443–6.Google Scholar
Di Bono, M. G., and Zorzi, M. 2013. ‘Deep Generative Learning of Location-Invariant Visual Word Recognition’. Frontiers in Psychology 4 (September): 635.CrossRefGoogle ScholarPubMed
DiCarlo, J. J., Zoccolan, D, and Rust, N. C.. 2012. ‘How Does the Brain Solve Visual Object Recognition?’ Neuron Perspective 73 (3): 415–34.Google ScholarPubMed
Di Liberto, G. M., Varghese, P, Kalashnikova, M, et al. 2018. ‘Atypical Cortical Entrainment to Speech in the Right Hemisphere Underpins Phonemic Deficits in Dyslexia’. NeuroImage 175 (July): 70–9.Google Scholar
Dingemans, M. M. L., van den, M Berg, and R. H. S. Westerink, . 2011. ‘Neurotoxicity of Brominated Flame Retardants: (In)direct Effects of Parent and Hydroxylated Polybrominated Diphenyl Ethers on the (Developing) Nervous System’. Environmental Health Perspectives 119 (7). https://doi.org/10.1289/ehp.1003035.CrossRefGoogle Scholar
Dingemans, M. M. L., Kock, M, and van den Berg, M. 2016. ‘Mechanisms of Action Point Towards Combined PBDE/NDL-PCB Risk Assessment’. Toxicological Sciences: An Official Journal of the Society of Toxicology 153 (2): 215–24.CrossRefGoogle ScholarPubMed
Di Nuovo, A., and Jay, T. 2019. ‘Development of Numerical Cognition in Children and Artificial Systems: A Review of the Current Knowledge and Proposals for Multi‐disciplinary Research’. Cognitive Computation and Systems 1 (1): 2–11.CrossRefGoogle Scholar
Dirks, E., Spyer, G, van Lieshout, E. C. D. M., and de Sonneville, L. 2008. ‘Prevalence of Combined Reading and Arithmetic Disabilities’. Journal of Learning Disabilities 41 (5): 460–73.CrossRefGoogle ScholarPubMed
Dodson, C. K., Travis, K. E., Borchers, L. R., et al. 2018. ‘White Matter Properties Associated with Pre-Reading Skills in 6-Year-Old Children Born Preterm and at Term’. Developmental Medicine and Child Neurology 60 (7): 695–702.Google Scholar
Doelling, K. B., Arnal, L. H., Ghitza, O, and Poeppel, D. 2014. ‘Acoustic Landmarks Drive Delta-Theta Oscillations to Enable Speech Comprehension by Facilitating Perceptual Parsing’. NeuroImage 85 Pt 2 (January): 761–8.CrossRefGoogle ScholarPubMed
Donald, K. A., Eastman, E, Howells, F. M, et al. 2015. ‘Neuroimaging Effects of Prenatal Alcohol Exposure on the Developing Human Brain: A Magnetic Resonance Imaging Review’. Acta Neuropsychiatrica 27 (5): 251–69.Google Scholar
D’Onofrio, B. M., Class, Q. A., Rickert, M. E., et al. 2016. ‘Translational Epidemiologic Approaches to Understanding the Consequences of Early-Life Exposures’. Behavior Genetics 46 (3): 315–28.Google Scholar
D’Onofrio, B. M., Singh, A. L., Iliadou, A, et al. 2010. ‘A Quasi-Experimental Study of Maternal Smoking during Pregnancy and Offspring Academic Achievement’. Child Development 81 (1): 80–100.Google Scholar
Donolato, E., Toffalini, E, Giofrè, D, Caviola, S, and Mammarella, I. C.. 2020. ‘Going beyond Mathematics Anxiety in Primary and Middle School Students: The Role of Ego‐resiliency in Mathematics’. Mind, Brain and Education: The Official Journal of the International Mind, Brain, and Education Society 14 (3): 255–66.CrossRefGoogle Scholar
Dowker, A., Sarkar, A, and Looi, C. Y. 2016. ‘Mathematics Anxiety: What Have We Learned in 60 Years?’ Frontiers in Psychology 7 (April): 508.Google Scholar
Downing, C., and Caravolas, M. 2020. ‘Prevalence and Cognitive Profiles of Children With Comorbid Literacy and Motor Disorders’. Frontiers in Psychology 11 (December): 573580.CrossRefGoogle ScholarPubMed
Dreger, R. M., and Aiken, L. R. Jr. 1957. ‘The Identification of Number Anxiety in a College Population’. Journal of Educational Psychology 48 (6): 344–51.CrossRefGoogle Scholar
Dreier, J. W., Berg-Beckhoff, G, Andersen, P. K, and Andersen, A.-M. N. 2017. ‘Prenatal Exposure to Fever and Infections and Academic Performance: A Multilevel Analysis’. American Journal of Epidemiology 186 (1): 29–37.CrossRefGoogle ScholarPubMed
Ducharme, S., Albaugh, M. D., Nguyen, T.-V, et al. 2016. ‘Trajectories of Cortical Thickness Maturation in Normal Brain Development: The Importance of Quality Control Procedures’. NeuroImage 125 (January): 267–79.CrossRefGoogle ScholarPubMed
Dumontheil, I., and Klingberg, T. 2012. ‘Brain Activity during a Visuospatial Working Memory Task Predicts Arithmetical Performance 2 Years Later’. Cerebral Cortex 22 (5): 1078–85.CrossRefGoogle ScholarPubMed
Duncan, L. E., and Keller, M. C.. 2011. ‘A Critical Review of the First 10 Years of Candidate Gene-by-Environment Interaction Research in Psychiatry’. The American Journal of Psychiatry 168 (10): 1041–9.CrossRefGoogle ScholarPubMed
Dunkel Schetter, C. 2011. ‘Psychological Science on Pregnancy: Stress Processes, Biopsychosocial Models, and Emerging Research Issues’. Annual Review of Psychology 62: 531–58.Google Scholar
Durston, S., and Casey, B. J.. 2006. ‘What Have We Learned about Cognitive Development from Neuroimaging?’ Neuropsychologia 44 (11): 2149–57.CrossRefGoogle ScholarPubMed
Eckert, M. A., Berninger, V. W., Vaden, K. I. Jr, Gebregziabher, M, and Tsu, L. 2016. ‘Gray Matter Features of Reading Disability: A Combined Meta-Analytic and Direct Analysis Approach(1,2,3,4)’. eNeuro 3 (1). https://doi.org/10.1523/ENEURO.0103-15.2015.Google Scholar
Eddins, D., Petro, A, Pollard, N, Freedman, J. H., and Levin, E. D.. 2008. ‘Mercury-Induced Cognitive Impairment in Metallothionein-1/2 Null Mice’. Neurotoxicology and Teratology 30 (2): 88–95.CrossRefGoogle ScholarPubMed
Eden, G. F., Jones, K. M., Cappell, K, et al. 2004. ‘Neural Changes Following Remediation in Adult Developmental Dyslexia’. Neuron 44 (3): 411–22.CrossRefGoogle ScholarPubMed
‘Education at a Glance 2018: OECD Indicators’. n.d. Accessed February 17, 2021. www.oecd-ilibrary.org/education/education-at-a-glance-2018_eag-2018-en.Google Scholar
EFSA n.d. ‘EFSA Provides Advice on the Safety and Nutritional Contribution of Wild and Farmed Fish’. n.d. Accessed July 16, 2021. www.efsa.europa.eu/en/news/efsa-provides-advice-safety-and-nutritional-contribution-wild-and-farmed-fish.Google Scholar
Ehrhart, F., Roozen, S, Verbeek, J, et al. 2019. ‘Review and Gap Analysis: Molecular Pathways Leading to Fetal Alcohol Spectrum Disorders’. Molecular Psychiatry 24 (1): 10–17.Google Scholar
Ehri, L. C. 2008. ‘Development of Sight Word Reading: Phases and Findings’. In Snowling, M. J and Hulme, C (eds.), The Science of Reading: A Handbook, 135–54. Blackwell Publishing Ltd.Google Scholar
Eicher, J. D., Powers, N. R., Cho, K, et al. 2013. ‘Associations of Prenatal Nicotine Exposure and the Dopamine Related Genes ANKK1 and DRD2 to Verbal Language’. PloS One 8 (5): e63762.CrossRefGoogle ScholarPubMed
Elman, J. L., Bates, E. A., Johnson, M. H., Parisi Karmiloff-Smith, A., Parisi, D., and Plunkett, K. 1996. Rethinking Innateness: A Connectionist Perspective on Development. MIT Press.Google Scholar
Elmore, R. F. 1979. Backward Mapping: Implementation Research and Policy Decisions. Political Science Quarterly 94 (4): 601–16.Google Scholar
Emerson, Robert W., and Cantlon, Jessica F.. 2012. ‘Early Math Achievement and Functional Connectivity in the Fronto-Parietal Network’. Developmental Cognitive Neuroscience 2 (1) (February): S139–51.CrossRefGoogle ScholarPubMed
Emerson, Robert W., and Cantlon, Jessica F. 2015. ‘Continuity and Change in Children’s Longitudinal Neural Responses to Numbers’. Developmental Science 18 (2): 314–26.CrossRefGoogle ScholarPubMed
EPA, US and OCSPP. 2015. ‘Polybrominated Diphenylethers (PBDEs) Significant New Use Rules (SNUR)’, September. www.epa.gov/assessing-and-managing-chemicals-under-tsca/polybrominated-diphenylethers-pbdes-significant-new-use.Google Scholar
EPA, US, and OLEM. 2013. ‘Technical Fact Sheet – Polybrominated Diphenyl Ethers (PBDEs) and Polybrominated Biphenyls (PBBs)’, July. www.epa.gov/fedfac/technical-fact-sheet-polybrominated-diphenyl-ethers-pbdes-and-polybrominated-biphenyls-pbbs.Google Scholar
EPA, US 2015. ‘Learn about Polychlorinated Biphenyls (PCBs),’ August. www.epa.gov/pcbs/learn-about-polychlorinated-biphenyls-pcbs.Google Scholar
EPA, US, and OP. 2016. ‘Biomonitoring: PBDEs – Report Contents,’ November. www.epa.gov/americaschildrenenvironment/biomonitoring-pbdes-report-contents.Google Scholar
Eskenazi, B., Chevrier, J, Rauch, S, et al. 2015. ‘In Utero and Childhood Polybrominated Diphenyl Ether (Pbde) Exposures and Neurodevelopment In The Chamacos Study’. Environmental Hazards and Neurodevelopment 121 (2): 257–62. https://doi.org/10.1201/b18030-18.CrossRefGoogle Scholar
Evans, T. M., Flowers, D. L, Luetje, M. M., Napoliello, E, and Eden, G. F.. 2016. ‘Functional Neuroanatomy of Arithmetic and Word Reading and Its Relationship to Age’. NeuroImage 143 (December): 304–15.CrossRefGoogle ScholarPubMed
Evans, T. M., Flowers, D. L, Napoliello, E. M., Olulade, O. A., and Eden, G. F.. 2014. ‘The Functional Anatomy of Single-Digit Arithmetic in Children with Developmental Dyslexia’. NeuroImage 101 (November): 644–52.CrossRefGoogle ScholarPubMed
Evans, T. M., Kochalka, J, Ngoon, T. J., et al. 2015. ‘Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children’s Numerical Abilities’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 35 (33): 11743–50.CrossRefGoogle ScholarPubMed
Evenhouse, E., and Reilly, S. 2005. ‘Improved Estimates of the Benefits of Breastfeeding Using Sibling Comparisons to Reduce Selection Bias’. Health Services Research 40 (6 Pt 1): 1781–802.Google Scholar
Evens, A., Hryhorczuk, D, Lanphear, B. P., et al. 2015. ‘The Impact of Low-Level Lead Toxicity on School Performance among Children in the Chicago Public Schools: A Population-Based Retrospective Cohort Study’. Environmental Health: A Global Access Science Source 14 (April): 21.CrossRefGoogle Scholar
Eysenck, M. W., and Calvo, M. G.. 1992. ‘Anxiety and Performance: The Processing Efficiency Theory’. Cognition and Emotion 6 (6): 409–34.CrossRefGoogle Scholar
Eysenck, M. W., Derakshan, N, Santos, R, and Calvo, M. G.. 2007. ‘Anxiety and Cognitive Performance: Attentional Control Theory’. Emotion 7 (2): 336–53.CrossRefGoogle ScholarPubMed
Facoetti, A., Corradi, N, Ruffino, M, Gori, S, and Zorzi, M. 2010. ‘Visual Spatial Attention and Speech Segmentation Are Both Impaired in Preschoolers at Familial Risk for Developmental Dyslexia’. Dyslexia 16 (3): 226–39.CrossRefGoogle ScholarPubMed
Facoetti, A., Trussardi, A. N, Ruffino, M, et al. 2010. ‘Multisensory Spatial Attention Deficits Are Predictive of Phonological Decoding Skills in Developmental Dyslexia’. Journal of Cognitive Neuroscience 22 (5): 1011–25.CrossRefGoogle ScholarPubMed
Fang, W.-Q., and Yuste, R. 2017. ‘Overproduction of Neurons Is Correlated with Enhanced Cortical Ensembles and Increased Perceptual Discrimination’. Cell Reports 21 (2): 381–92.CrossRefGoogle ScholarPubMed
Fang, M., Zhou, Z., Chen, S., and McClelland, J.. 2018. Can a Recurrent Neural Network Learn to Count Things? In Proceedings of the 40th Annual Meeting of the Cognitive Science Society, https://stanford.edu/~jlmcc/papers/FangZhouChenMcC18Count.pdfGoogle Scholar
Faramarzi, S. and Sadri, S.. 2014. The Effect of Basic Neuropsychological Interventions on Performance of Students with Dyscalculia. Neuropsychiatria i Neuropsychologia. 9. 48–54.Google Scholar
Farina, M., Rocha, J. B. T., and Aschner, M. 2011. ‘Mechanisms of Methylmercury-Induced Neurotoxicity: Evidence from Experimental Studies’. Life Sciences 89 (15-16): 555–63.CrossRefGoogle ScholarPubMed
Fawcett, A. J., Nicolson, R. I., and Dean, P.. 1996. ‘Impaired Performance of Children with Dyslexia on a Range of Cerebellar Tasks’. Annals of Dyslexia 46 (1): 259–83.CrossRefGoogle ScholarPubMed
Fayol, M., Zorman, M, and Bernard, L. 2009. ‘Associations and Dissociations in Reading and Spelling French: Unexpectedly Poor and Good Spellers’. British Journal of Educational Psychology 2: 63–75. https://doi.org/10.1348/000709909x421973.Google Scholar
Feigenson, L., Dehaene, S, and Spelke, E. 2004. ‘Core Systems of Number’. Trends in Cognitive Sciences 8 (7): 307–14.CrossRefGoogle ScholarPubMed
Felleman, D. J., and Van Essen, D. C.. 1991. ‘Distributed Hierarchical Processing in the Primate Cerebral Cortex’. Cerebral Cortex 1 (1): 1–47.CrossRefGoogle ScholarPubMed
Feng, X., Altarelli, I, Monzalvo, K, et al. 2020. ‘A Universal Reading Network and Its Modulation by Writing System and Reading Ability in French and Chinese Children’. eLife 9 (October). https://doi.org/10.7554/eLife.54591.CrossRefGoogle ScholarPubMed
Fergusson, D. M., Beautrais, A. L., and Silva, P. A.. 1982. ‘Breast-Feeding and Cognitive Development in the First Seven Years of Life’. Social Science & Medicine 16 (19): 1705–8.Google Scholar
Ferrer, E., McArdle, J. J., Shaywitz, B. A., et al. 2007. ‘Longitudinal Models of Developmental Dynamics between Reading and Cognition from Childhood to Adolescence’. Developmental Psychology 43 (6): 1460–73.CrossRefGoogle ScholarPubMed
Fias, W., Menon, V, and Szűcs, D. 2013. ‘Multiple Components of Developmental Dyscalculia’. Trends in Neuroscience and Education 2 (2): 43–7.CrossRefGoogle Scholar
Fields, R. D. 2015. ‘A New Mechanism of Nervous System Plasticity: Activity-Dependent Myelination’. Nature Reviews. Neuroscience 16 (12): 756–67.Google Scholar
Figueiró-Filho, E. A., Croy, B. A., Reynolds, J. N., et al. 2017. ‘Diffusion Tensor Imaging of White Matter in Children Born from Preeclamptic Gestations’. AJNR. American Journal of Neuroradiology 38 (4): 801–6.CrossRefGoogle ScholarPubMed
Finnish Basic Education Act (2010). Perusopetuslain muutokset 642/2010 [Amendments to the Finnish Basic Education Act].Google Scholar
Finnish National Agency for Education (2017). Support in Basic Education.Google Scholar
Flak, A. L., Su, S, Bertrand, J, et al. 2014. ‘The Association of Mild, Moderate, and Binge Prenatal Alcohol Exposure and Child Neuropsychological Outcomes: A Meta-Analysis’. Alcoholism, Clinical and Experimental Research 38 (1): 214–26.CrossRefGoogle ScholarPubMed
Flanagan, S., and Goswami, U. 2018. ‘The Role of Phase Synchronisation between Low Frequency Amplitude Modulations in Child Phonology and Morphology Speech Tasks’. The Journal of the Acoustical Society of America 143 (3): 1366.CrossRefGoogle ScholarPubMed
Flaugnacco, E., Lopez, L, Terribili, C, et al. 2015. ‘Music Training Increases Phonological Awareness and Reading Skills in Developmental Dyslexia: A Randomized Control Trial’. PloS One 10 (9): e0138715.CrossRefGoogle ScholarPubMed
Fleming, R. W., and Storrs, K. R.. 2019. ‘Learning to See Stuff’. Current Opinion in Behavioral Sciences 30 (December): 100–8.CrossRefGoogle ScholarPubMed
Fletcher, J. M., and MiciakJ, J.. 2019. The Identification of Specific Learning Disabilities: A Summary of Research on Best Practices. Meadows Center for Preventing Educational Risk.Google Scholar
Flore, P. C., and Wicherts, J. M.. 2015. ‘Does Stereotype Threat Influence Performance of Girls in Stereotyped Domains? A Meta-Analysis’. Journal of School Psychology 53 (1): 25–44.CrossRefGoogle ScholarPubMed
Formisano, E., and Kriegeskorte, N. 2012. ‘Seeing Patterns through the Hemodynamic Veil – The Future of Pattern-Information fMRI’. NeuroImage 62 (2): 1249–56. https://doi.org/10.1016/j.neuroimage.2012.02.078.Google Scholar
Forray, A. 2016. ‘Substance Use during Pregnancy’. F1000Research 5 (May). https://doi.org/10.12688/f1000research.7645.1.CrossRefGoogle ScholarPubMed
Fraga, G., Gorka, G. Zarić, J. Tijms, et al. 2014. ‘Brain-Potential Analysis of Visual Word Recognition in Dyslexics and Typically Reading Children’. Frontiers in Human Neuroscience 8 (June): 474.Google Scholar
Franceschini, S., and Bertoni, S. 2019. ‘Improving Action Video Games Abilities Increases the Phonological Decoding Speed and Phonological Short-Term Memory in Children with Developmental Dyslexia’. Neuropsychologia 130 (July): 100–6.CrossRefGoogle ScholarPubMed
Franceschini, S., Bertoni, S, Ronconi, L, et al. 2015. “Shall We Play a Game?”: Improving Reading Through Action Video Games in Developmental Dyslexia’. Current Developmental Disorders Reports 2 (4): 318–29.Google Scholar
Franceschini, S., Trevisan, P, Ronconi, L, et al. 2017. ‘Action Video Games Improve Reading Abilities and Visual-to-Auditory Attentional Shifting in English-Speaking Children with Dyslexia’. Scientific Reports 7 (1): 5863.CrossRefGoogle ScholarPubMed
Franke, K., Van den Bergh, B. R. H., et al. 2020. ‘Effects of Maternal Stress and Nutrient Restriction during Gestation on Offspring Neuroanatomy in Humans’. Neuroscience and Biobehavioral Reviews 117 (October): 5–25.CrossRefGoogle ScholarPubMed
Frankland, P. W., and Bontempi, B. 2005. ‘The Organization of Recent and Remote Memories’. Nature Reviews. Neuroscience 6 (2): 119–30.CrossRefGoogle ScholarPubMed
Frederiksen, M., Vorkamp, K, Thomsen, M, and Knudsen, L. E.. 2009. ‘Human Internal and External Exposure to PBDEs–a Review of Levels and Sources’. International Journal of Hygiene and Environmental Health 212 (2): 109–34.CrossRefGoogle ScholarPubMed
Fried, P. A., and Smith, A. M.. 2001. ‘A Literature Review of the Consequences of Prenatal Marihuana Exposure. An Emerging Theme of a Deficiency in Aspects of Executive Function’. Neurotoxicology and Teratology 23 (1): 1–11.Google Scholar
Fried, P. A., Watkinson, B., and Siegel, L. S.. 1997. ‘Reading and Language in 9- to 12-Year Olds Prenatally Exposed to Cigarettes and Marijuana’. Neurotoxicology and Teratology 19 (3): 171–83.Google ScholarPubMed
Fried, P. A., Watkinson, B, and Gray, R. 2003. ‘Differential Effects on Cognitive Functioning in 13- to 16-Year-Olds Prenatally Exposed to Cigarettes and Marihuana’. Neurotoxicology and Teratology 25 (4): 427–36.CrossRefGoogle ScholarPubMed
Friguls, B., Joya, X, Garcia-Serra, J, et al. 2012. ‘Assessment of Exposure to Drugs of Abuse during Pregnancy by Hair Analysis in a Mediterranean Island’. Addiction 107 (8): 1471–9.CrossRefGoogle Scholar
Frith, U. 1985. Beneath the Surface of Developmental Dyslexia. Developmental Dyslexia. 13.Google Scholar
Frith, U. 1998. ‘Literally Changing the Brain’. Brain: A Journal of Neurology 121 (Pt 6) (June): 1011–12.CrossRefGoogle ScholarPubMed
Froyen, D. J. W., Bonte, M. L., van Atteveldt, N, and Blomert, L. 2009. ‘The Long Road to Automation: Neurocognitive Development of Letter-Speech Sound Processing’. Journal of Cognitive Neuroscience 21 (3): 567–80.CrossRefGoogle Scholar
Frye, R. E., Hasan, K, Malmberg, B, et al. 2010. ‘Superior Longitudinal Fasciculus and Cognitive Dysfunction in Adolescents Born Preterm and at Term’. Developmental Medicine and Child Neurology 52 (8): 760–6.CrossRefGoogle ScholarPubMed
Fryer, S. L., Mattson, S. N., Jernigan, T. L., et al. 2012. ‘Caudate Volume Predicts Neurocognitive Performance in Youth with Heavy Prenatal Alcohol Exposure’. Alcoholism, Clinical and Experimental Research 36 (11): 1932–41.CrossRefGoogle ScholarPubMed
Fryer, S. L., Tapert, S. F., Mattson, S. N., et al. 2007. ‘Prenatal Alcohol Exposure Affects Frontal-Striatal BOLD Response during Inhibitory Control’. Alcoholism, Clinical and Experimental Research 31 (8): 1415–24.CrossRefGoogle ScholarPubMed
Fuchs, E., and Flügge, G. 2014. ‘Adult Neuroplasticity: More than 40 Years of Research’. Neural Plasticity 2014 (May): 541870.Google Scholar
Fuchs, L. S., Geary, D. C., Compton, D. L., et al. 2013. ‘Effects of First-Grade Number Knowledge Tutoring With Contrasting Forms of Practice’. Journal of Educational Psychology 105 (1): 58–77.CrossRefGoogle ScholarPubMed
Fuchs, L. S., Powell, S. R., Hamlett, C. L., et al. 2008. ‘Remediating Computational Deficits at Third Grade: A Randomized Field Trial’. Journal of Research on Educational Effectiveness 1 (1): 2–32.CrossRefGoogle Scholar
Fuchs, L. S., Powell, S. R., Seethaler, P. M., et al. 2009. ‘Remediating Number Combination and Word Problem Deficits Among Students With Mathematics Difficulties: A Randomized Control Trial’. Journal of Educational Psychology 101 (3): 561–76.CrossRefGoogle ScholarPubMed
Fuchs, L. S., Powell, S. R., Seethaler, P. M., et al. 2010. ‘A Framework for Remediating Number Combination Deficits’. Exceptional Children 76 (2): 135–65.CrossRefGoogle ScholarPubMed
Fujioka, T., Fujioka, A., Tan, N., et al. 2001. ‘Mild Prenatal Stress Enhances Learning Performance in the Non-Adopted Rat Offspring’. Neuroscience 103 (2): 301–7.CrossRefGoogle ScholarPubMed
Fürst, C. 1999. Die Rolle der Lehrkraft im Gruppenunterricht. In H.-D. Dann, T. Diegritz, and H. S. Rosenbusch (eds.), Gruppenunterricht im Schulalltag. Realität und Chancen, 107–50. Universitätsbund Erlangen-Nürnberg e.V.Google Scholar
Gabel, L. A., Gibson, C. J., Gruen, J. R., and LoTurco, J. J.. 2010. ‘Progress towards a Cellular Neurobiology of Reading Disability’. Neurobiology of Disease 38 (2): 173–80. https://doi.org/10.1016/j.nbd.2009.06.019.CrossRefGoogle ScholarPubMed
Gallit, F., Wyschkon, A, Poltz, N, et al. 2018. ‘Henne Oder Ei: Reziprozität Mathematischer Vorläufer Und Vorhersage Des Rechnens’. Lernen Und Lernstörungen 7 (2): 81–92.CrossRefGoogle Scholar
Gangl, M., Moll, K, Jones, M. W., et al. 2018. ‘Lexical Reading in Dysfluent Readers of German’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 22 (1): 24–40.Google Scholar
Garnelo, M., and Shanahan, M. 2019. ‘Reconciling Deep Learning with Symbolic Artificial Intelligence: Representing Objects and Relations’. Current Opinion in Behavioral Sciences 29 (October): 17–23.CrossRefGoogle Scholar
Garry, A., Rigourd, V, Amirouche, A, et al. 2009. ‘Cannabis and Breastfeeding’. Journal of Toxicology 2009 (April): 596149.CrossRefGoogle ScholarPubMed
Gauthier, I., Skudlarski, P., Gore, J. C., and Anderson, A. W.. 2000. ‘Expertise for Cars and Birds Recruits Brain Areas Involved in Face Recognition’. Nature Neuroscience 3 (2): 191–7.CrossRefGoogle ScholarPubMed
Geary, D. C., Hoard, M. K., Byrd-Craven, J, et al. 2007. ‘Cognitive Mechanisms Underlying Achievement Deficits in Children with Mathematical Learning Disability’. Child Development 78 (4): 1343–59.CrossRefGoogle ScholarPubMed
Geary, D. C., Hoard, M. K., Nugent, L, and D. Bailey, H.. 2012. ‘Mathematical Cognition Deficits in Children With Learning Disabilities and Persistent Low Achievement: A Five-Year Prospective Study’. Journal of Educational Psychology 104 (1): 206–23.CrossRefGoogle ScholarPubMed
Geary, D. C., Bow-Thomas, C. C., and Yao, Y.. 1992. ‘Counting Knowledge and Skill in Cognitive Addition: A Comparison of Normal and Mathematically Disabled Children’. Journal of Experimental Child Psychology 54 (3): 372–91.CrossRefGoogle ScholarPubMed
Geary, D. C., Hamson, C. O., and Hoard, M. K.. 2000. ‘Numerical and Arithmetical Cognition: A Longitudinal Study of Process and Concept Deficits in Children with Learning Disability’. Journal of Experimental Child Psychology 77 (3): 236–63.CrossRefGoogle ScholarPubMed
Geary, D. C., Hoard, M. K., and Hamson, C. O.. 1999. ‘Numerical and Arithmetical Cognition: Patterns of Functions and Deficits in Children at Risk for a Mathematical Disability’. Journal of Experimental Child Psychology 74 (3): 213–39.CrossRefGoogle ScholarPubMed
Gebauer, D., Fink, A, Kargl, R, et al. 2012. ‘Differences in Brain Function and Changes with Intervention in Children with Poor Spelling and Reading Abilities’. PloS One 7 (5): e38201.CrossRefGoogle ScholarPubMed
Gentle, S. J., Travers, C. P., and Carlo, W. A.. 2018. ‘Caffeine Controversies’. Current Opinion in Pediatrics 30 (2): 177–81.CrossRefGoogle ScholarPubMed
Georgiou, G. K., Protopapas, A, Papadopoulos, T. C., Skaloumbakas, C, and Parrila, R. 2010. ‘Auditory Temporal Processing and Dyslexia in an Orthographically Consistent Language’. Cortex 46 (10): 1330–44. https://doi.org/10.1016/j.cortex.2010.06.006.CrossRefGoogle Scholar
Gerlach, M., Fritz, A., Ricken, G., Schmidt, S. 2007. Kalkulie. Diagnose- und Trainingsprogramm für rechenschwache Kinder. Cornelsen.Google Scholar
Germanò, E., Gagliano, A, and Curatolo, P. 2010. ‘Comorbidity of ADHD and Dyslexia’. Developmental Neuropsychology 35 (5): 475–93.CrossRefGoogle ScholarPubMed
Germano, G. D., Reilhac, C, Capellini, S. A., and Valdois, S. 2014. ‘The Phonological and Visual Basis of Developmental Dyslexia in Brazilian Portuguese Reading Children’. Frontiers in Psychology 5 (October): 1169.CrossRefGoogle ScholarPubMed
Gialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, Na, et al. 2020. ‘Genome-Wide Association Study Reveals New Insights into the Heritability and Genetic Correlates of Developmental Dyslexia’. Molecular Psychiatry, 26: 3004–17. https://doi.org/10.1038/s41380-020-00898-x.Google ScholarPubMed
Gibbons, L., Belizán, J. M., Lauer, J. A., et al. 2010. ‘The Global Numbers and Costs of Additionally Needed and Unnecessary Caesarean Sections Performed per Year: Overuse as a Barrier to Universal Coverage’. World Health Report 30 (1): 1–31.Google Scholar
Gibson, E. M., Purger, D., Mount, C. W., et al. 2014. ‘Neuronal Activity Promotes Oligodendrogenesis and Adaptive Myelination in the Mammalian Brain’. Science 344 (6183): 480–1.CrossRefGoogle ScholarPubMed
Giménez, M., Miranda, M. J., P. Born, A., et al. 2008. ‘Accelerated Cerebral White Matter Development in Preterm Infants: A Voxel-Based Morphometry Study with Diffusion Tensor MR Imaging’. NeuroImage 41 (3): 728–34.CrossRefGoogle ScholarPubMed
Giofrè, D., Borella, E, and Mammarella, I. C. 2017. ‘The Relationship between Intelligence, Working Memory, Academic Self-Esteem, and Academic Achievement’. Journal of Cognitive Psychology 29 (6): 731–47.CrossRefGoogle Scholar
Giraud, A.-L., and Poeppel, D. 2012. ‘Cortical Oscillations and Speech Processing: Emerging Computational Principles and Operations’. Nature Neuroscience 15 (4): 511–17.CrossRefGoogle ScholarPubMed
Giraud, A.-L., and Ramus, F. 2013. ‘Neurogenetics and Auditory Processing in Developmental Dyslexia’. Current Opinion in Neurobiology 23 (1): 37–42.CrossRefGoogle ScholarPubMed
Glass, L., Graham, D. M., Akshoomoff, N, and Mattson, S. N.. 2015. ‘Cognitive Factors Contributing to Spelling Performance in Children with Prenatal Alcohol Exposure’. Neuropsychology 29 (6): 817–28.CrossRefGoogle ScholarPubMed
Glass, L., Moore, E. M., Akshoomoff, N, et al. 2017. ‘Academic Difficulties in Children with Prenatal Alcohol Exposure: Presence, Profile, and Neural Correlates’. Alcoholism, Clinical and Experimental Research 41 (5): 1024–34.Google Scholar
Glezer, L. S., Jiang, X, and Riesenhuber, M.. 2009. ‘Evidence for Highly Selective Neuronal Tuning to Whole Words in the “Visual Word Form Area.”’ Neuron 62 (2): 199–204.CrossRefGoogle ScholarPubMed
Glezer, L. S., Kim, J, Rule, J, Jiang, X, and Riesenhuber, M. 2015. ‘Adding Words to the Brain’s Visual Dictionary: Novel Word Learning Selectively Sharpens Orthographic Representations in the VWFA’. Journal of Neuroscience 35 (12): 4965–72.CrossRefGoogle Scholar
Glover, V. 2015. ‘Prenatal Stress and Its Effects on the Fetus and the Child: Possible Underlying Biological Mechanisms’. Advances in Neurobiology 10: 269–83.Google Scholar
Gobel, S.M., and Snowling, M.J.. 2010. ‘Number-Processing Skills in Adults with Dyslexia’. Quarterly Journal of Experimental Psychology 63 (7): 1361–73.CrossRefGoogle ScholarPubMed
Göbel, S. M., Watson, S. E., Lervåg, A, and Hulme, C. 2014. ‘Children’s Arithmetic Development’. Psychological Science 25 (3): 789–98. https://doi.org/10.1177/0956797613516471.CrossRefGoogle ScholarPubMed
Goetz, T., Bieg, M, Lüdtke, O, Pekrun, R, and Hall, N. C.. 2013. ‘Do Girls Really Experience More Anxiety in Mathematics?’ Psychological Science 24 (10): 2079–87.CrossRefGoogle ScholarPubMed
Goffin, C., and Ansari, D. 2016. ‘Beyond Magnitude: Judging Ordinality of Symbolic Number Is Unrelated to Magnitude Comparison and Independently Relates to Individual Differences in Arithmetic’. Cognition 150 (May): 68–76.CrossRefGoogle ScholarPubMed
Goldenberg, R. L., Culhane, J. F., Iams, J. D., and Romero, R. 2008. ‘Epidemiology and Causes of Preterm Birth’. The Lancet 371 (9606): 75–84.CrossRefGoogle ScholarPubMed
Goldschmidt, L., Richardson, G. A., Cornelius, M. D., and Day, N. L.. 2004. ‘Prenatal Marijuana and Alcohol Exposure and Academic Achievement at Age 10’. Neurotoxicology and Teratology 26 (4): 521–32.Google Scholar
Goldschmidt, L., Richardson, G. A., Willford, J. A., Severtson, S. G., and Day, N. L.. 2012. ‘School Achievement in 14-Year-Old Youths Prenatally Exposed to Marijuana’. Neurotoxicology and Teratology 34 (1): 161–7.CrossRefGoogle ScholarPubMed
Goldschmidt, L., Richardson, G. A., Willford, J, and Day, N. L.. 2008. ‘Prenatal Marijuana Exposure and Intelligence Test Performance at Age 6’. Journal of the American Academy of Child and Adolescent Psychiatry 47 (3): 254–63.Google Scholar
Gomez, J., Barnett, M, and Grill-Spector, K. 2019. ‘Extensive Childhood Experience with Pokémon Suggests Eccentricity Drives Organization of Visual Cortex’. Nature Human Behaviour 3 (6): 611–24.Google Scholar
Gonda, Y., Andrews, W. D., Tabata, H, et al. 2013. ‘Robo1 Regulates the Migration and Laminar Distribution of Upper-Layer Pyramidal Neurons of the Cerebral Cortex’. Cerebral Cortex 23 (6): 1495–508. https://doi.org/10.1093/cercor/bhs141.CrossRefGoogle ScholarPubMed
Gonzalez, F. F., and Miller, S. P.. 2006. ‘Does Perinatal Asphyxia Impair Cognitive Function without Cerebral Palsy?’ Archives of Disease in Childhood. Fetal and Neonatal Edition 91 (6): F454–9.Google Scholar
Goodfellow, I., Bengio, Y, and Courville, A. 2016. Deep Learning. MIT Press.Google Scholar
Goodlett, C. R., and Horn, K. H (2001). ‘Mechanisms of Alcohol-Induced Damage to the Developing Nervous System’. Alcohol Research and Health: The Journal of the National Institute on Alcohol Abuse and Alcoholism, 25 (3), 175–84. https://pubs.niaaa.nih.gov/publications/arh25-3/175-184.htm.Google Scholar
Gori, S., Cecchini, P, Bigoni, A, Molteni, M, and Facoetti, A. 2014. ‘Magnocellular-Dorsal Pathway and Sub-Lexical Route in Developmental Dyslexia’. Frontiers in Human Neuroscience 8 (June): 460.CrossRefGoogle ScholarPubMed
Gori, S., Mascheretti, S, Giora, E, et al. 2015. ‘The DCDC2 Intron 2 Deletion Impairs Illusory Motion Perception Unveiling the Selective Role of Magnocellular-Dorsal Stream in Reading (dis)ability’. Cerebral Cortex 25 (6): 1685–95.Google Scholar
Goswami, U. 2011. ‘A Temporal Sampling Framework for Developmental Dyslexia’. Trends in Cognitive Sciences 15 (1): 3–10.CrossRefGoogle ScholarPubMed
Goswami, U 2015a. ‘Sensory Theories of Developmental Dyslexia: Three Challenges for Research’. Nature Reviews. Neuroscience 16 (1): 43–54.CrossRefGoogle ScholarPubMed
Goswami, U 2015b. ‘Visual Attention Span Deficits and Assessing Causality in Developmental Dyslexia’. Nature Reviews: Neuroscience 16: 225–6.CrossRefGoogle Scholar
Goswami, U 2018. ‘A Neural Basis for Phonological Awareness? An Oscillatory Temporal-Sampling Perspective’. Current Directions in Psychological Science 27 (1): 56–63.CrossRefGoogle Scholar
Goswami, U 2019a. ‘A Neural Oscillations Perspective on Phonological Development and Phonological Processing in Developmental Dyslexia’. Language and Linguistics Compass 13 (5): e12328.CrossRefGoogle Scholar
Goswami, U 2019b. ‘Speech Rhythm and Language Acquisition: An Amplitude Modulation Phase Hierarchy Perspective’. Annals of the New York Academy of Sciences 1453 (1): 67–78.Google Scholar
Goswami, U 2020a. ‘Reading Acquisition and Developmental Dyslexia: Educational Neuroscience and Phonological Skills’. In Thomas, M. S. C., Mareschal, D., and Dumontheil, I. (eds.), Educational Neuroscience: Development across the Lifespan, pp. 144–68. Routledge.Google Scholar
Goswami, U 2020b. ‘Toward Realizing the Promise of Educational Neuroscience: Improving Experimental Design in Developmental Cognitive Neuroscience Studies’. Annual Review of Developmental Psychology 2 (1): 133–55.CrossRefGoogle Scholar
Goswami, U., Huss, M, Mead, N, and Fosker, T. 2021. ‘Auditory Sensory Processing and Phonological Development in High IQ and Exceptional Readers, Typically Developing Readers, and Children With Dyslexia: A Longitudinal Study’. Child Development 92 (3): 1083–98.CrossRefGoogle ScholarPubMed
Goswami, U., Huss, M, Mead, N, Fosker, T, and Verney, J. P.. 2013. ‘Perception of Patterns of Musical Beat Distribution in Phonological Developmental Dyslexia: Significant Longitudinal Relations with Word Reading and Reading Comprehension’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 49 (5): 1363–76.Google Scholar
Goswami, U., Mead, N, Fosker, T, et al. 2013. ‘Impaired Perception of Syllable Stress in Children with Dyslexia: A Longitudinal Study’. Journal of Memory and Language 69 (1): 1–17.Google Scholar
Goswami, U., Power, A. J., Lallier, M, and Facoetti, A. 2014. ‘Oscillatory ‘Temporal Sampling’ and Developmental Dyslexia: Toward an Over-arching Theoretical Framework’. Frontiers in Human Neuroscience 8 (November): 904.CrossRefGoogle ScholarPubMed
Goswami, U., Sharon Wang, H-L, Cruz, A., et al. 2011. ‘Language-Universal Sensory Deficits in Developmental Dyslexia: English, Spanish, and Chinese’. Journal of Cognitive Neuroscience 23 (2): 325–37.Google Scholar
Grabner, R. H., Ansari, D, Koschutnig, K, et al. 2009. ‘To Retrieve or to Calculate? Left Angular Gyrus Mediates the Retrieval of Arithmetic Facts during Problem Solving’. Neuropsychologia 47 (2): 604–8.CrossRefGoogle ScholarPubMed
Grabner, R. H., Ansari, D, Reishofer, G, et al. 2007. ‘Individual Differences in Mathematical Competence Predict Parietal Brain Activation during Mental Calculation’. NeuroImage 38 (2): 346–56.CrossRefGoogle ScholarPubMed
Grabner, R. H., Ischebeck, A, Reishofer, G, et al. 2009. ‘Fact Learning in Complex Arithmetic and Figural-Spatial Tasks: The Role of the Angular Gyrus and Its Relation to Mathematical Competence’. Human Brain Mapping 30 (9): 2936–52.CrossRefGoogle ScholarPubMed
Graham, A. M., Marr, M, Buss, C, Sullivan, E. L., and Fair, D. A.. 2021. ‘Understanding Vulnerability and Adaptation in Early Brain Development Using Network Neuroscience’. Trends in Neurosciences 44 (4): 276–88.Google Scholar
Grandjean, P., and Landrigan, P. J.. 2014. ‘Neurobehavioural Effects of Developmental Toxicity’. Lancet Neurology 13 (3): 330–8.Google Scholar
Grandjean, P., Weihe, P., White, R. F., et al. 1997. ‘Cognitive Deficit in 7-Year-Old Children with Prenatal Exposure to Methylmercury’. Neurotoxicology and Teratology 19 (6): 417–28.Google Scholar
Grant, J. G., Siegel, L. S., and D’Angiulli, A. 2020. ‘From Schools to Scans: A Neuroeducational Approach to Comorbid Math and Reading Disabilities’. Frontiers in Public Health 8 (October): 469.CrossRefGoogle ScholarPubMed
Grant, K. S., Petroff, R, Isoherranen, N, Stella, N, and Burbacher, T. M.. 2018. ‘Cannabis Use during Pregnancy: Pharmacokinetics and Effects on Child Development’. Pharmacology & Therapeutics 182 (February): 133–51.CrossRefGoogle ScholarPubMed
Gray, S. (2015). The Effects of Morpho-Phonemic and Whole Word Instruction on the Literacy Skills of Adult Struggling Readers. City University of New York.Google Scholar
Gray, K. A., Klebanoff, M. A., Brock, J. W., et al. 2005. ‘In Utero Exposure to Background Levels of Polychlorinated Biphenyls and Cognitive Functioning among School-Age Children’. American Journal of Epidemiology 162 (1): 17–26.CrossRefGoogle ScholarPubMed
Grayson, D. S., and Fair, D. A.. 2017. ‘Development of Large-Scale Functional Networks from Birth to Adulthood: A Guide to the Neuroimaging Literature’. NeuroImage 160 (October): 15–31.CrossRefGoogle Scholar
Greicius, M. D., Krasnow, B., Reiss, A. L., and Menon, V.. 2003. ‘Functional Connectivity in the Resting Brain: A Network Analysis of the Default Mode Hypothesis’. Proceedings of the National Academy of Sciences 100 (1): 253–8. https://doi.org/10.1073/pnas.0135058100.CrossRefGoogle Scholar
Grills, A. E., Fletcher, J. M., Vaughn, S, et al. 2014. ‘Anxiety and Response to Reading Intervention among First Grade Students’. Child & Youth Care Forum 43 (4): 417–31.Google Scholar
Grill-Spector, K., and Weiner, K. S.. 2014. ‘The Functional Architecture of the Ventral Temporal Cortex and Its Role in Categorization’. Nature Reviews. Neuroscience 15 (8): 536–48.CrossRefGoogle ScholarPubMed
Grills-Taquechel, A. E., Fletcher, J. M., Vaughn, S. R., and Stuebing, K. K.. 2012. ‘Anxiety and Reading Difficulties in Early Elementary School: Evidence for Unidirectional- or Bi-Directional Relations?’ Child Psychiatry and Human Development 43 (1): 35–47.CrossRefGoogle ScholarPubMed
Groeschel, S., Tournier, J.-D, Northam, G. B., et al. 2014. ‘Identification and Interpretation of Microstructural Abnormalities in Motor Pathways in Adolescents Born Preterm’. NeuroImage 87 (February): 209–19.CrossRefGoogle ScholarPubMed
Gross, J., Hoogenboom, N, Thut, G, et al. 2013. ‘Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain’. PLoS Biology 11 (12): e1001752.CrossRefGoogle ScholarPubMed
Grump, K. S., Kjellstrom, T., Shipp, A. M., Silvers, A., and Stewart, A.. 1998. ‘Influence of Prenatal Mercury Exposure upon Scholastic and Psychologica Test Performance: Benchmark Analysis of a New Zealand Cohort’. Risk Analysis: An Official Publication of the Society for Risk Analysis 18 (6): 701–13.Google Scholar
Gu, S., Satterthwaite, T. D., Medaglia, J. D., et al. 2015. ‘Emergence of System Roles in Normative Neurodevelopment’. Proceedings of the National Academy of Sciences of the United States of America 112 (44): 13681–6.Google ScholarPubMed
Gullick, M. M., and Booth, J. R.. 2015. ‘The Direct Segment of the Arcuate Fasciculus Is Predictive of Longitudinal Reading Change’. Developmental Cognitive Neuroscience 13 (June): 68–74.Google Scholar
Gulson, B. L., Mizon, K. J., Korsch, M. J., et al. 1996. ‘Impact on Blood Lead in Children and Adults Following Relocation from Their Source of Exposure and Contribution of Skeletal Tissue to Blood Lead’. Bulletin of Environmental Contamination and Toxicology 56 (4): 543–50.Google ScholarPubMed
Gumusoglu, S. B., Chilukuri, A. S. S., Saantillan, D. A, et al. 2020. ‘Neurodevelopmental Outcomes of Prenatal Preeclampsia Exposure’. Trends in Neurosciences 43 (4): 253–68.CrossRefGoogle ScholarPubMed
Guttorm, T. K., Leppänen, P. H. T., Hämäläinen, J. A, et al. 2010. ‘Newborn Event-Related Potentials Predict Poorer Pre-Reading Skills in Children at Risk for Dyslexia’. Journal of Learning Disabilities 43 (5): 391–401.CrossRefGoogle ScholarPubMed
Habermann, S., Donlan, C, Göbel, S. M., and Hulme, C. 2020. ‘The Critical Role of Arabic Numeral Knowledge as a Longitudinal Predictor of Arithmetic Development’. Journal of Experimental Child Psychology 193 (May): 104794.Google Scholar
Haberstroh, S., and Schulte-Körne, G. 2019. ‘The Diagnosis and Treatment of Dyscalculia’. Deutsches Arzteblatt International 116 (7): 107–14.Google ScholarPubMed
Halberda, J., and Feigenson, L. 2008. ‘Developmental Change in the Acuity of the ‘Number Sense’: The Approximate Number System in 3-, 4-, 5-, and 6-Year-Olds and Adults’. Developmental Psychology 44 (5): 1457–65.CrossRefGoogle ScholarPubMed
Halberda, J., Ly, R, Wilmer, J. B., Naiman, D. Q., and Germine, L. 2012. ‘Number Sense across the Lifespan as Revealed by a Massive Internet-Based Sample’. Proceedings of the National Academy of Sciences of the United States of America 109 (28): 11116–20.Google ScholarPubMed
Halberda, J., Mazzocco, M. M. M., and Feigenson, L. 2008. ‘Individual Differences in Non-Verbal Number Acuity Correlate with Maths Achievement’. Nature 455 (7213): 665–8.Google Scholar
Halpern, D., Beninger, A., and Straight, C.. 2011. ‘Sex Differences in Intelligence’. In R. Sternberg and S. Kaufman (eds.), The Cambridge Handbook of Intelligence, 253–72). Cambridge University Press. doi:10.1017/CBO9780511977244.014CrossRefGoogle Scholar
Hancock, R., Pugh, K. R., and Hoeft, F. 2017. ‘Neural Noise Hypothesis of Developmental Dyslexia’. Trends in Cognitive Sciences 21 (6): 434–48.Google Scholar
Handel, M. van, Swaab, H, de Vries, L. S., and Jongmans, M. J.. 2007. ‘Long-Term Cognitive and Behavioral Consequences of Neonatal Encephalopathy Following Perinatal Asphyxia: A Review’. European Journal of Pediatrics 166 (7): 645–54.Google ScholarPubMed
Handler, S. M., Fierson, W. M., and the Section on Ophthalmology and Council on Children with Disabilities, American Academy of Ophthalmology, American Association for Pediatric Ophthalmology and Strabismus, and American Association of Certified Orthoptists. 2011. ‘Learning Disabilities, Dyslexia, and Vision’. Pediatrics 127 (3): e818–56.CrossRefGoogle ScholarPubMed
Hanf, K. 1982. ‘The Implementation of Regulatory Policy’. Journal of Political Research, 1982.Google Scholar
Hanich, L. B., Jordan, N. C., Kaplan, D, and Dick, J. 2001. ‘Performance across Different Areas of Mathematical Cognition in Children with Learning Difficulties’. Journal of Educational Psychology 93 (3): 615–26. https://doi.org/10.1037/0022-0663.93.3.615.Google Scholar
Hannagan, T., Amedi, A, Cohen, L, Dehaene-Lambertz, G, and Dehaene, S. 2015. ‘Origins of the Specialization for Letters and Numbers in Ventral Occipitotemporal Cortex’. Trends in Cognitive Sciences 19 (7): 374–82.CrossRefGoogle ScholarPubMed
Hannagan, T., Ziegler, J. C., Dufau, S., Fagot, J., and Grainger, J.. 2014. ‘Deep Learning of Orthographic Representations in Baboons’. PloS One 9 (1): e84843.CrossRefGoogle ScholarPubMed
Harada, M. 1995. ‘Minamata Disease: Methylmercury Poisoning in Japan Caused by Environmental Pollution’. Critical Reviews in Toxicology 25 (1): 1–24.CrossRefGoogle ScholarPubMed
Harlaar, N., Dale, P. S., and Plomin, R.. 2007. ‘From Learning to Read to Reading to Learn: Substantial and Stable Genetic Influence’. Child Development 78 (1): 116–31.CrossRefGoogle ScholarPubMed
Harlaar, N., Deater-Deckard, K., Thompson, L. A., Dethorne, L. S., and Petrill, S. A.. 2011. ‘Associations between Reading Achievement and Independent Reading in Early Elementary School: A Genetically Informative Cross-Lagged Study’. Child Development 82 (6): 2123–37.CrossRefGoogle Scholar
Harlaar, N., Spinath, F. M., Dale, P. S., and Plomin, R.. 2005. ‘Genetic Influences on Early Word Recognition Abilities and Disabilities: A Study of 7-Year-Old Twins’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 46 (4): 373–84.Google Scholar
Harlaar, N., Trzaskowski, M., Dale, P. S., and Plomin, R.. 2014. ‘Word Reading Fluency: Role of Genome-Wide Single-Nucleotide Polymorphisms in Developmental Stability and Correlations with Print Exposure’. Child Development 85 (3): 1190–205.CrossRefGoogle ScholarPubMed
Harm, M. W., and Seidenberg, M. S.. 2004. ‘Computing the Meanings of Words in Reading: Cooperative Division of Labor between Visual and Phonological Processes’. Psychological Review 111 (3): 662–720.CrossRefGoogle ScholarPubMed
Harm, M. W., and Seidenberg, M. S.. 1999. ‘Phonology, Reading Acquisition, and Dyslexia: Insights from Connectionist Models’. Psychological Review 106 (3): 491–528.CrossRefGoogle ScholarPubMed
Harris, J. J., Reynell, C., and Attwell, D.. 2011. ‘The Physiology of Developmental Changes in BOLD Functional Imaging Signals’. Developmental Cognitive Neuroscience 1 (3): 199–216.Google Scholar
Hart, S. A., Little, C., and van Bergen, E.. 2021. ‘Nurture Might Be Nature: Cautionary Tales and Proposed Solutions’. NPJ Science of Learning 6 (1): 2.Google Scholar
Hasko, S., Groth, K., Bruder, J., Bartling, J., and Schulte-Körne, G.. 2013. ‘The Time Course of Reading Processes in Children with and without Dyslexia: An ERP Study’. Frontiers in Human Neuroscience 7 (October): 570.CrossRefGoogle ScholarPubMed
Haworth, C. M. A., Kovas, Y., Harlaar, N., et al. 2009. ‘Generalist Genes and Learning Disabilities: A Multivariate Genetic Analysis of Low Performance in Reading, Mathematics, Language and General Cognitive Ability in a Sample of 8000 12-Year-Old Twins’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 50 (10): 1318–25.Google Scholar
Hayatbakhsh, M. R., Flenady, V. J., Gibbons, K. S., et al. 2012. ‘Birth Outcomes Associated with Cannabis Use before and during Pregnancy’. Pediatric Research 71 (2): 215–19.Google Scholar
Hay, D. F., Pawlby, S., Waters, C. S., and Sharp, D.. 2008. ‘Antepartum and Postpartum Exposure to Maternal Depression: Different Effects on Different Adolescent Outcomes’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 49 (10): 1079–88.Google Scholar
Hay, D. F., Pawlby, S., Sharp, D., et al. 2001. ‘Intellectual Problems Shown by 11-Year-Old Children Whose Mothers Had Postnatal Depression’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 42 (7): 871–89.Google Scholar
Health Canada. 2009. ‘Prenatal Nutrition Guidelines for Health Professionals – Fish and Omega-3 Fatty Acids’. April 28, 2009. www.canada.ca/en/health-canada/services/publications/food-nutrition/prenatal-nutrition-guidelines-health-professionals-fish-omega-3-fatty-acids-2009.html.Google Scholar
Hedges, L. V., and Olkin, I.. 1985. Statistical Methods for Meta-Analysis. Academic PressGoogle Scholar
Heikkilä, K., Kelly, Y., Renfrew, M. J., Sacker, A., and Quigley, M. A.. 2014. ‘Breastfeeding and Educational Achievement at Age 5’. Maternal & Child Nutrition 10 (1): 92–101.Google Scholar
Heim, S., Pape-Neumann, J., van Ermingen-Marbach, M., Brinkhaus, M., and Grande, M.. 2015. ‘Shared vs. Specific Brain Activation Changes in Dyslexia after Training of Phonology, Attention, or Reading’. Brain Structure & Function 220 (4): 2191–207.CrossRefGoogle ScholarPubMed
Heinonen, K., Eriksson, J. G., Kajantie, Eero, et al. 2013. ‘Late-Preterm Birth and Lifetime Socioeconomic Attainments: The Helsinki Birth Cohort Study’. Pediatrics 132 (4): 647–55.CrossRefGoogle ScholarPubMed
Hembree, R. 1990. ‘The Nature, Effects, and Relief of Mathematics Anxiety’. Journal for Research in Mathematics Education 21 (1): 33–46.Google Scholar
Hensler, B. S., Schatschneider, C., Taylor, J., and Wagner, R. K.. 2010. ‘Behavioral Genetic Approach to the Study of Dyslexia’. Journal of Developmental and Behavioral Pediatrics: JDBP 31 (7): 525–32.Google Scholar
Hernandez-Miranda, L. R., Cariboni, A., Faux, C., et al. 2011. ‘Robo1 Regulates Semaphorin Signaling to Guide the Migration of Cortical Interneurons through the Ventral Forebrain’. Journal of Neuroscience 31 (16): 6174–87. https://doi.org/10.1523/jneurosci.5464-10.2011.Google Scholar
Herting, M. M., Gautam, P., Chen, Z., Mezher, A., and Vetter, N. C.. 2018. ‘Test-Retest Reliability of Longitudinal Task-Based fMRI: Implications for Developmental Studies’. Developmental Cognitive Neuroscience 33 (October): 17–26.Google Scholar
Hervais-Adelman, A., Kumar, U, Mishra, R. K., et al. 2019. ‘Learning to Read Recycles Visual Cortical Networks without Destruction’. Science Advances 10.Google Scholar
Higginbotham, H., Eom, T.-Y, Mariani, L. E., et al. 2012. ‘Arl13b in Primary Cilia Regulates the Migration and Placement of Interneurons in the Developing Cerebral Cortex’. Developmental Cell 23 (5): P925–38. https://doi.org/10.1016/j.devcel.2012.09.019.Google Scholar
Higuera-Matas, A., Ucha, M., and Ambrosio, E.. 2015. ‘Long-Term Consequences of Perinatal and Adolescent Cannabinoid Exposure on Neural and Psychological Processes’. Neuroscience and Biobehavioral Reviews 55 (August): 119–46.CrossRefGoogle ScholarPubMed
Hill, F., Mammarella, I. C., Devine, A., et al. 2016. ‘Maths Anxiety in Primary and Secondary School Students: Gender Differences, Developmental Changes and Anxiety Specificity’. Learning and Individual Differences 48 (May): 45–53.Google Scholar
Hill, S. Y., Lowers, L., Locke-Wellman, J., and Shen, S. A.. 2000. ‘Maternal Smoking and Drinking during Pregnancy and the Risk for Child and Adolescent Psychiatric Disorders’. Journal of Studies on Alcohol 61 (5): 661–8.CrossRefGoogle ScholarPubMed
Hinshelwood, J. 1896. ‘A Case Of Dyslexia: A Peculiar Form Of Word-Blindness.’. The Lancet 148 (3821): 1451–4.Google Scholar
Hinton, G., Deng, L., Yu, D., et al. 2012. ‘Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups’. IEEE Signal Processing Magazine 29 (6): 82–97.Google Scholar
Hinton, G. E. 2007. ‘Learning Multiple Layers of Representation’. Trends in Cognitive Sciences 11 (10): 428–34.CrossRefGoogle ScholarPubMed
Hinton, G. E., and Sejnowski, T. J.. 1999. Unsupervised Learning: Foundations of Neural Computation. MIT Press.CrossRefGoogle Scholar
Hoeft, F., McCandliss, B. D., Black, J. M., et al. 2011. ‘Neural Systems Predicting Long-Term Outcome in Dyslexia’. Proceedings of the National Academy of Sciences of the United States of America 108 (1): 361–6.Google ScholarPubMed
Hoeft, F., Meyler, A., Hernandez, A., et al. 2007. ‘Functional and Morphometric Brain Dissociation between Dyslexia and Reading Ability’. Proceedings of the National Academy of Sciences of the United States of America 104 (10): 4234–9.Google Scholar
Hohnen, B., and Stevenson, J.. 1999. ‘The Structure of Genetic Influences on General Cognitive, Language, Phonological, and Reading Abilities’. Developmental Psychology 35 (2): 590–603.CrossRefGoogle ScholarPubMed
Hokkanen, L., Launes, J., and Michelsson, K.. 2014. ‘Adult Neurobehavioral Outcome of Hyperbilirubinemia in Full Term Neonates-a 30 Year Prospective Follow-up Study’. PeerJ 2 (March): e294.Google Scholar
Holland, E. B., Goldstone, J. V., Pessah, I. N., et al. 2017. ‘Ryanodine Receptor and FK506 Binding Protein 1 in the Atlantic Killifish (Fundulus Heteroclitus): A Phylogenetic and Population-Based Comparison’. Aquatic Toxicology 192 (November): 105–15.CrossRefGoogle ScholarPubMed
Holloway, I. D., and Ansari, D.. 2009. ‘Mapping Numerical Magnitudes onto Symbols: The Numerical Distance Effect and Individual Differences in Children’s Mathematics Achievement’. Journal of Experimental Child Psychology 103 (1): 17–29. https://doi.org/10.1016/j.jecp.2008.04.001.Google Scholar
Holloway, I. D., and Ansari, D. 2010. ‘Developmental Specialization in the Right Intraparietal Sulcus for the Abstract Representation of Numerical Magnitude’. Journal of Cognitive Neuroscience 22 (11): 2627–37.CrossRefGoogle ScholarPubMed
Hopko, D. R., Mahadevan, R, Bare, R. L., and Hunt, M. K.. 2003. ‘The Abbreviated Math Anxiety Scale (AMAS): Construction, Validity, and Reliability’. Assessment 10 (2): 178–82.Google Scholar
Hopko, D. R., Ashcraft, M. H., Gute, J., Ruggiero, K. J., and Lewis, C.. 1998. ‘Mathematics Anxiety and Working Memory: Support for the Existence of a Deficient Inhibition Mechanism’. Journal of Anxiety Disorders 12 (4): 343–55.Google Scholar
Horsfield, M. A., and Jones, D. K.. 2002. ‘Applications of Diffusion-Weighted and Diffusion Tensor MRI to White Matter Diseases: A Review’. NMR in Biomedicine 15 (7–8): 570–7.Google Scholar
Horta, B., Bahl, L., Rajiv, J. C. Martinés, C. G. Victora, Cesar and World Health Organization. 2007. Evidence on The Long-Term Effects of Breastfeeding: Systematic Review and Meta-Analyses. World Health Organization. https://apps.who.int/iris/handle/10665/43623.Google Scholar
Horta, B. L., de Mola, C. L., and Victora, C. G.. 2015. ‘Breastfeeding and Intelligence: A Systematic Review and Meta-Analysis’. Acta Paediatrica 104 (467): 14–19.CrossRefGoogle ScholarPubMed
Horwitz, E. K. 1986. ‘Preliminary Evidence for the Reliability and Validity of a Foreign Language Anxiety Scale’. TESOL Quarterly 20 (3): 559–62.Google Scholar
Horwitz, E. K., Horwitz, M. B., and Cope, J.. 1986. ‘Foreign Language Classroom Anxiety’. The Modern Language Journal 70 (2): 125–32.Google Scholar
Horwood, L. J., and Fergusson, D. M.. 1998. ‘Breastfeeding and Later Cognitive and Academic Outcomes’. Pediatrics 101 (1): E9.Google Scholar
Houdé, O., Rossi, S., Lubin, A., and Joliot, M. 2010. ‘Mapping Numerical Processing, Reading, and Executive Functions in the Developing Brain: An fMRI Meta-Analysis of 52 Studies Including 842 Children’. Developmental Science 13 (6): 876–85.CrossRefGoogle Scholar
Houston, S. M., Lebel, C., Katzir, T, et al. 2014. ‘Reading Skill and Structural Brain Development’. Neuroreport 25 (5): 347–52.Google Scholar
Howell, K. K., Lynch, M. E., Platzman, K. A., Smith, G. H, and Coles, C. D.. 2006. ‘Prenatal Alcohol Exposure and Ability, Academic Achievement, and School Functioning in Adolescence: A Longitudinal Follow-Up’. Journal of Pediatric Psychology 31 (1): 116–26.CrossRefGoogle ScholarPubMed
Hubbard, E. M., Piazza, M., Pinel, P., and Dehaene, S.. 2005. ‘Interactions between Number and Space in Parietal Cortex’. Nature Reviews. Neuroscience 6 (6): 435–48.Google Scholar
Huber, E., Donnelly, P. M., Rokem, A., and Yeatman, J. D.. 2018. ‘Rapid and Widespread White Matter Plasticity during an Intensive Reading Intervention’. Nature Communications 9 (1): 2260.Google Scholar
Huettig, F., Kolinsky, R., and Lachmann, T.. 2018. ‘The Culturally Co-Opted Brain: How Literacy Affects the Human Mind’. Language, Cognition and Neuroscience 33 (3): 275–7.Google Scholar
Huettig, F., Lachmann, T., Reis, A., and Petersson, K. M.. 2018. ‘Distinguishing Cause from Effect – Many Deficits Associated with Developmental Dyslexia May Be a Consequence of Reduced and Suboptimal Reading Experience’. Language, Cognition and Neuroscience 33 (3): 333–50.Google Scholar
Hughes, C. A., O’Gorman, L. A., Shyr, Y., et al. 1999. ‘Cognitive Performance at School Age of Very Low Birth Weight Infants with Bronchopulmonary Dysplasia’. Journal of Developmental and Behavioral Pediatrics: JDBP 20 (1): 1–8.Google Scholar
Huizink, A. C., and Mulder, E. J. H.. 2006. ‘Maternal Smoking, Drinking or Cannabis Use during Pregnancy and Neurobehavioral and Cognitive Functioning in Human Offspring’. Neuroscience and Biobehavioral Reviews 30 (1): 24–41.Google Scholar
Hulme, C., Nash, H. M., Gooch, D., Lervåg, A., and Snowling, M. J.. 2015. ‘The Foundations of Literacy Development in Children at Familial Risk of Dyslexia’. Psychological Science 26 (12): 1877–86.Google Scholar
Hulme, C., and Snowling, M. J.. 2016. ‘Reading Disorders and Dyslexia’. Current Opinion in Pediatrics 28 (6): 731–5.CrossRefGoogle ScholarPubMed
Huss, M., Verney, J. P., Fosker, T., Mead, N., and Goswami, U.. 2011. ‘Music, Rhythm, Rise Time Perception and Developmental Dyslexia: Perception of Musical Meter Predicts Reading and Phonology’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 47 (6): 674–89.Google Scholar
Hutton, J. S., Dudley, J., Horowitz-Kraus, T., DeWitt, T., and Holland, S. K.. 2020. ‘Associations between Home Literacy Environment, Brain White Matter Integrity and Cognitive Abilities in Preschool-Age Children’. Acta Paediatrica 109 (7): 1376–86.Google Scholar
Hutton, J. S., Horowitz-Kraus, T., Mendelsohn, A. L., et al. 2015. ‘Home Reading Environment and Brain Activation in Preschool Children Listening to Stories’. Pediatrics 136 (3): 466–78.CrossRefGoogle ScholarPubMed
Hutton, J. S., Phelan, K., Horowitz-Kraus, T., et al. 2017. ‘Shared Reading Quality and Brain Activation during Story Listening in Preschool-Age Children’. The Journal of Pediatrics 191 (December): 204–11.Google Scholar
Hu, Y., Geng, F., Tao, L., et al. 2011. ‘Enhanced White Matter Tracts Integrity in Children with Abacus Training’. Human Brain Mapping 32 (1): 10–21.CrossRefGoogle ScholarPubMed
Hyde, J. S., Fennema, E., Ryan, M., Frost, L. A., and Hopp, C.. 1990. Gender Comparisons of Mathematics Attitudes and Affect: A Meta-Analysis. Psychology of Women Quarterly 14 (3): 299–324.Google Scholar
Ialongo, N., Edelsohn, G., Werthamer-Larsson, L., Crockett, L., and Kellam, S.. 1994. ‘The Significance of Self-Reported Anxious Symptoms in First-Grade Children’. Journal of Abnormal Child Psychology 22 (4): 441–55.CrossRefGoogle ScholarPubMed
IDEA. 2019 Annual Report to Congress on the Individuals with Disabilities Education Act (IDEA). https://sites.ed.gov/idea/2019-annual-report-to-congress-IDEA/Google Scholar
Infant and Young Child Feeding. 2018. Seventy-First World Health Assembly Agenda item 12.6; 26 May: https://apps.who.int/iris/bitstream/handle/10665/279517/A71_R9-en.pdf.Google Scholar
Isaacs, E. B., Edmonds, C. J., Lucas, A., and Gadian, D. G.. 2001. ‘Calculation Difficulties in Children of Very Low Birthweight: A Neural Correlate’. Brain: A Journal of Neurology 124 (Pt 9): 1701–7.Google Scholar
Isaacs, E. B., Fischl, B. R., Quinn, B. T., et al. 2010. ‘Impact of Breast Milk on Intelligence Quotient, Brain Size, and White Matter Development’. Pediatric Research 67 (4): 357–62.Google Scholar
Ischebeck, A., Zamarian, L., Schocke, M., and Delazer, M.. 2009. ‘Flexible Transfer of Knowledge in Mental Arithmetic–an fMRI Study’. NeuroImage 44 (3): 1103–12.Google Scholar
Ischebeck, A., Zamarian, L., Siedentopf, C., et al. 2006. ‘How Specifically Do We Learn? Imaging the Learning of Multiplication and Subtraction’. NeuroImage 30 (4): 1365–75.Google Scholar
Ishibashi, T., Dakin, K. A., Stevens, B., et al. 2006. ‘Astrocytes Promote Myelination in Response to Electrical Impulses’. Neuron 49 (6): 823–32.CrossRefGoogle ScholarPubMed
Iuculano, T. 2016. ‘Neurocognitive Accounts of Developmental Dyscalculia and Its Remediation’. In Progress in Brain Research, edited by Cappelletti, M and Fias, W, 227:305–33. Elsevier.Google Scholar
Iuculano, T., and Menon, V.. 2018. ‘Development of Mathematical Reasoning’. In Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, 1–40. John Wiley & Sons, Inc. https://doi.org/10.1002/9781119170174.epcn406.Google Scholar
Iuculano, T., Padmanabhan, A., and Menon, V.. 2018. ‘Systems Neuroscience of Mathematical Cognition and Learning: Basic Organization and Neural Sources of Heterogeneity in Typical and Atypical Development’. In Heterogeneity of Function in Numerical Cognition, edited by Henik, A. and Fias, W., 287–336. Academic Press.Google Scholar
Iuculano, ,., Rosenberg-Lee, M., Richardson, J., et al. 2015. ‘Cognitive Tutoring Induces Widespread Neuroplasticity and Remediates Brain Function in Children with Mathematical Learning Disabilities’. Nature Communications 6 (8453). https://doi.org/10.1038/ncomms9453.Google Scholar
Iuculano, T., Tang, J., Hall, C. W. B., and Butterworth, B.. 2008. ‘Core Information Processing Deficits in Developmental Dyscalculia and Low Numeracy’. Developmental Science 11 (5): 669–80.Google Scholar
Izard, V., Sann, C., Spelke, E. S., and Streri, A.. 2009. ‘Newborn Infants Perceive Abstract Numbers’. Proceedings of the National Academy of Sciences of the United States of America 106 (25): 10382–5.Google Scholar
Jacobson, J. L., Dodge, N. C., Burden, M. J., Klorman, R., and Jacobson, S. W.. 2011. ‘Number Processing in Adolescents with Prenatal Alcohol Exposure and ADHD: Differences in the Neurobehavioral Phenotype’. Alcoholism, Clinical and Experimental Research 35 (3): 431–42.Google Scholar
Jacobson, J. L., and Jacobson, S. W.. 2002. ‘Effects of Prenatal Alcohol Exposure on Child Development’. Alcohol Research & Health: The Journal of the National Institute on Alcohol Abuse and Alcoholism 26 (4): 282–6.Google Scholar
Jaekel, J., Baumann, N., and Wolke, D.. 2013. ‘Effects of Gestational Age at Birth on Cognitive Performance: A Function of Cognitive Workload Demands’. PloS One 8 (5): e65219.CrossRefGoogle ScholarPubMed
Jalongo, M. R., and Hirsh, R. A.. 2010. ‘Understanding Reading Anxiety: New Insights from Neuroscience’. Early Childhood Education Journal 37 (6): 431–5.Google Scholar
James, K. H. 2010. ‘Sensori-Motor Experience Leads to Changes in Visual Processing in the Developing Brain’. Developmental Science 13 (2): 279–88.Google Scholar
Jaques, S. C., Kingsbury, A., Henshcke, P., et al. 2014. ‘Cannabis, the Pregnant Woman and Her Child: Weeding out the Myths’. Journal of Perinatology: Official Journal of the California Perinatal Association 34 (6): 417–24.Google Scholar
Jarlenski, M., Barry, C. L., Gollust, S., et al. 2017. ‘Polysubstance Use Among US Women of Reproductive Age Who Use Opioids for Nonmedical Reasons’. American Journal of Public Health 107 (8): 1308–10.CrossRefGoogle ScholarPubMed
Jensen, A. R. 1998. The G Factor: The Science of Mental Ability. Praeger Publishers/Greenwood Publishing Group.Google Scholar
Jirikowic, T., Kartin, D., and Carmichael, H Olson, . 2008. ‘Children with Fetal Alcohol Spectrum Disorders: A Descriptive Profile of Adaptive Function’. Canadian Journal of Occupational Therapy. Revue Canadienne D’ergotherapie 75 (4): 238–48.Google Scholar
Johansen-Berg, H., and Behrens, T. E. J.. 2006. ‘Just Pretty Pictures? What Diffusion Tractography Can Add in Clinical Neuroscience’. Current Opinion in Neurology 19 (4): 379–85.Google Scholar
Jolles, D., Ashkenazi, S., Kochalka, J., et al. 2016. ‘Parietal Hyper-Connectivity, Aberrant Brain Organization, and Circuit-Based Biomarkers in Children with Mathematical Disabilities’. Developmental Science 19 (4): 613–31.Google Scholar
Jolles, D., Supekar, K., Richardson, J., et al. 2016. ‘Reconfiguration of Parietal Circuits with Cognitive Tutoring in Elementary School Children’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 83 (October): 231–45.Google Scholar
Jolles, D., Wassermann, D., Chokhani, R., et al. 2016. ‘Plasticity of Left Perisylvian White-Matter Tracts Is Associated with Individual Differences in Math Learning’. Brain Structure & Function 221 (3): 1337–51.Google Scholar
Joo, S. J., Tavabi, K., and Yeatman, J. D.. 2019. ‘Automaticity in the Reading Circuitry’. Cold Spring Harbor Laboratory. https://doi.org/10.1101/829937.Google Scholar
Jordan, N. C., Hanich, L. B., and Kaplan, D.. 2003a. ‘A Longitudinal Study of Mathematical Competencies in Children with Specific Mathematics Difficulties versus Children with Comorbid Mathematics and Reading Difficulties’. Child Development 74 (3): 834–50.Google Scholar
Jordan, N. C., Hanich, L. B., and Kaplan, D. 2003b. ‘Arithmetic Fact Mastery in Young Children: A Longitudinal Investigation’. Journal of Experimental Child Psychology 85 (2): 103–19.Google Scholar
Jordan, N. C., Kaplan, D., Ramineni, C., and Locuniak, M. N.. 2009. ‘Early Math Matters: Kindergarten Number Competence and Later Mathematics Outcomes’. Developmental Psychology 45 (3): 850–67. https://doi.org/10.1037/a0014939.Google Scholar
Jordan, N. C., and Montani, T. O.. 1997. ‘Cognitive Arithmetic and Problem Solving’. Journal of Learning Disabilities 30 (6): 624–34. https://doi.org/10.1177/002221949703000606.Google Scholar
Joyner, R. E., and Wagner, R. K.. 2020. ‘Co-Occurrence of Reading Disabilities and Math Disabilities: A Meta-Analysis’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 24 (1): 14–22.Google Scholar
Kadosh, R. C., and Walsh, V.. 2009. ‘Numerical Representation in the Parietal Lobes: Abstract or Not Abstract?’ Behavioral and Brain Sciences 32 (3-4): 313–28. https://doi.org/10.1017/s0140525x09990938.Google Scholar
Kalashnikova, M., Burnham, D, and Goswami, U. 2020. ‘The Role of Paired Associate Learning in Acquiring Letter-Sound Correspondences: A Longitudinal Study of Children at Family Risk for Dyslexia’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading, December, 1–15.Google Scholar
Kalashnikova, M., Goswami, U, and Burnham, D. 2018. ‘Mothers Speak Differently to Infants at-Risk for Dyslexia’. Developmental Science 21 (1). https://doi.org/10.1111/desc.12487.Google Scholar
Kalashnikova, M., Goswami, U, and Burnham, D 2019a. ‘Delayed Development of Phonological Constancy in Toddlers at Family Risk for Dyslexia’. Infant Behavior & Development 57 (November): 101327.Google Scholar
Kalashnikova, M., Goswami, U, and Burnham, D 2019b. ‘Sensitivity to Amplitude Envelope Rise Time in Infancy and Vocabulary Development at 3 Years: A Significant Relationship’. Developmental Science 22 (6): e12836.CrossRefGoogle ScholarPubMed
Kalashnikova, M., Goswami, U, and Burnham, D 2020. ‘Novel Word Learning Deficits in Infants at Family Risk for Dyslexia’. Dyslexia 26 (1): 3–17.CrossRefGoogle ScholarPubMed
Kamijo, S., Ishii, Y, Horigane, S.-I, et al. 2018. ‘A Critical Neurodevelopmental Role for L-Type Voltage-Gated Calcium Channels in Neurite Extension and Radial Migration’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 38 (24): 5551–66.Google Scholar
Karipidis, I. I., Pleisch, G., Brandeis, D, et al. 2018. ‘Simulating Reading Acquisition: The Link between Reading Outcome and Multimodal Brain Signatures of Letter-Speech Sound Learning in Prereaders’. Scientific Reports 8 (1): 7121.Google Scholar
Kasala, S., Briyal, S, Prazad, P, et al. 2020. ‘Exposure to Morphine and Caffeine Induces Apoptosis and Mitochondrial Dysfunction in a Neonatal Rat Brain’. Frontiers in Pediatrics 8 (September): 593.CrossRefGoogle Scholar
Katzir, T., Kim, Y.-S. G., and Dotan, S. 2018. ‘Reading Self-Concept and Reading Anxiety in Second Grade Children: The Roles of Word Reading, Emergent Literacy Skills, Working Memory and Gender’. Frontiers in Psychology 9 (July): 1180.Google Scholar
Kaufmann, L., Wood, G, Rubinsten, O, and Henik, A. 2011. ‘Meta-Analyses of Developmental fMRI Studies Investigating Typical and Atypical Trajectories of Number Processing and Calculation’. Developmental Neuropsychology 36 (6): 763–87.Google Scholar
Kaufmann, L., Mazzocco, M. M., Dowker, A., et al. 2013. ‘Dyscalculia from a Developmental and Differential Perspective’. Frontiers in Psychology 4 (August): 516.Google Scholar
Kaufmann, L. Vogel, S. E., Starke, M., et al. 2009. ‘Developmental Dyscalculia: Compensatory Mechanisms in Left Intraparietal Regions in Response to Nonsymbolic Magnitudes’. Behavioral and Brain Functions: BBF 5 (August): 35.Google Scholar
Kaufmann, L., Vogel, S. E., Wood, G, et al. 2008. ‘A Developmental fMRI Study of Nonsymbolic Numerical and Spatial Processing’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 44 (4): 376–85.Google Scholar
Kaufmann, L., Vogel, S. E., Starke, M., Kremser, C., and Schocke, M.. 2009. ‘Numerical and Non-Numerical Ordinality Processing in Children with and without Developmental Dyscalculia: Evidence from fMRI’. Cognitive Development 24 (4): 486–94.Google Scholar
Kazemi, T., Huang, S, Avci, N. G., et al. 2020. ‘Investigating the Influence of Perinatal Nicotine and Alcohol Exposure on the Genetic Profiles of Dopaminergic Neurons in the VTA Using miRNA-mRNA Analysis’. Scientific Reports 10 (1): 15016.Google Scholar
Keller, T. A., and Adam, Marcel Just. 2009. ‘Altering Cortical Connectivity: Remediation-Induced Changes in the White Matter of Poor Readers’. Neuron 64 (5): 624–31.Google Scholar
Kelly, C. E., Cheong, J. L. Y., Fam, L. G, et al. 2016. ‘Moderate and Late Preterm Infants Exhibit Widespread Brain White Matter Microstructure Alterations at Term-Equivalent Age Relative to Term-Born Controls’. Brain Imaging and Behavior 10 (1): 41–9.Google Scholar
Kendler, K. S., Neale, M., Kessler, R., Heath, A., and Eaves, L.. 1993. ‘A Twin Study of Recent Life Events and Difficulties’. Archives of General Psychiatry 50 (10): 789–96.Google Scholar
Kermani, M., Verghese, A, and Vidyasagar, T. R.. 2018. ‘Attentional Asymmetry between Visual Hemifields Is Related to Habitual Direction of Reading and Its Implications for Debate on Cause and Effects of Dyslexia’. Dyslexia 24 (1): 33–43.Google Scholar
Kerper, L. E., Ballatori, N., and Clarkson, T. W.. 1992. ‘Methylmercury Transport across the Blood-Brain Barrier by an Amino Acid Carrier’. The American Journal of Physiology 262 (5 Pt 2): R761–5.Google Scholar
Kerr-Wilson, C. O., Mackay, D. F., Smith, G. C. S., and Pell, J. P.. 2012. ‘Meta-Analysis of the Association between Preterm Delivery and Intelligence’. Journal of Public Health 34 (2): 209–16.CrossRefGoogle ScholarPubMed
Kersey, A. J., Wakim, K.-.M, Li, R., and Cantlon, J. F.. 2019. ‘Developing, Mature, and Unique Functions of the Child’s Brain in Reading and Mathematics’. Developmental Cognitive Neuroscience 39 (October): 100684.CrossRefGoogle ScholarPubMed
Kevan, A., and Pammer, K. 2008. ‘Making the Link between Dorsal Stream Sensitivity and Reading’. Neuroreport 19 (4): 467–70.Google Scholar
Kevan, A., and Pammer, K 2009. ‘Predicting Early Reading Skills from Pre-Reading Measures of Dorsal Stream Functioning’. Neuropsychologia 47 (14): 3174–81.Google Scholar
Khwaja, O., and Volpe, J. J.. 2008. ‘Pathogenesis of Cerebral White Matter Injury of Prematurity’. Archives of Disease in Childhood. Fetal and Neonatal Edition 93 (2): F153–61.Google Scholar
Kim, D., and Thayer, S. A.. 2001. ‘Cannabinoids Inhibit the Formation of New Synapses between Hippocampal Neurons in Culture’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 21 (10): RC146.Google Scholar
Kim, G., Jang, J, Baek, S, Song, M, and Paik, S.-B. 2021. ‘Visual Number Sense in Untrained Deep Neural Networks’. Science Advances 7 (1): eabd6127.CrossRefGoogle ScholarPubMed
Kim, K. H., Bose, D. D., Ghogha, A, et al. 2011. ‘Para- and Ortho -Substitutions Are Key Determinants of Polybrominated Diphenyl Ether Activity toward Ryanodine Receptors and Neurotoxicity’. Environmental Health Perspectives 119 (4). https://doi.org/10.1289/ehp.1002728.Google Scholar
King, K. M., Littlefield, A. K., McCabe, C. J., et al. 2018. ‘Longitudinal Modeling in Developmental Neuroimaging Research: Common Challenges, and Solutions from Developmental Psychology’. Developmental Cognitive Neuroscience 33 (October): 54–72.Google Scholar
Klebanoff, M. A., and Keim, S.A.. 2015. ‘Maternal Caffeine Intake During Pregnancy and Child Cognition and Behavior at 4 and 7 Years of Age’. American Journal of Epidemiology 182 (12): 1023–32.Google Scholar
Klein, E., Willmes, K, Bieck, S. M., Bloechle, J, and Moeller, K. 2019. ‘White Matter Neuro-Plasticity in Mental Arithmetic: Changes in Hippocampal Connectivity Following Arithmetic Drill Training’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 114 (May): 115–23.Google Scholar
Klingberg, T., Hedehus, M., Temple, E., et al. 2000. ‘Microstructure of Temporo-Parietal White Matter as a Basis for Reading Ability: Evidence from Diffusion Tensor Magnetic Resonance Imaging’. Neuron 25 (2): 493–500.Google Scholar
Knight, M. J., Smith-Collins, A, Newell, S, Denbow, M, and Kauppinen, R. A.. 2018. ‘Cerebral White Matter Maturation Patterns in Preterm Infants: An MRI T2 Relaxation Anisotropy and Diffusion Tensor Imaging Study’. Journal of Neuroimaging: Official Journal of the American Society of Neuroimaging 28 (1): 86–94.Google Scholar
Knopik, V. S., Neiderhiser, J. M., DeFries, J. C., and Plomin, R. 2016. Behavioral Genetics. Macmillan Higher Education.Google Scholar
Kodavanti, P. R. S. 2017. ‘Polychlorinated Biphenyls (PCBs)☆’. Reference Module in Neuroscience and Biobehavioral Psychology. Elsevier.Google Scholar
Kohonen, T. 1990. ‘The Self-Organizing Map’. Proceedings of the IEEE 78 (9): 1464–80.CrossRefGoogle Scholar
Koletzko, B., Agostoni, C., Carlson, S. E., et al. 2007. ‘Long Chain Polyunsaturated Fatty Acids (LC-PUFA) and Perinatal Development’. Acta Paediatrica 90 (4): 460–4.Google Scholar
Kolkman, M. E., Kroesbergen, E. H., and Leseman, P.P. M.. 2013. ‘Early Numerical Development and the Role of Non-Symbolic and Symbolic Skills’. Learning and Instruction 25 (June): 95–103.Google Scholar
Kondracki, A. J. 2019. ‘Prevalence and Patterns of Cigarette Smoking before and during Early and Late Pregnancy according to Maternal Characteristics: The First National Data Based on the 2003 Birth Certificate Revision, United States, 2016’. Reproductive Health 16 (1): 142.Google Scholar
Koponen, T., Aro, M, Poikkeus, A.-M, et al. 2018. ‘Comorbid Fluency Difficulties in Reading and Math: Longitudinal Stability Across Early Grades’. Exceptional Children. https://doi.org/10.1177/0014402918756269.Google Scholar
Koponen, T., Eklund, K, Heikkilä, R, et al. 2020. ‘Cognitive Correlates of the Covariance in Reading and Arithmetic Fluency: Importance of Serial Retrieval Fluency’. Child Development 91 (4): 1063–80.Google Scholar
Koren, G. 1995. ‘Fetal Toxicology of Environmental Tobacco Smoke’. Current Opinion in Pediatrics 7 (2): 128–31.CrossRefGoogle ScholarPubMed
Kotimäki, S., Härkönen, J, Karlsson, L, Karlsson, H, and Scheinin, N. M.. 2020. ‘Educational Differences in Prenatal Anxiety and Depressive Symptoms and the Role of Childhood Circumstances’. SSM – Population Health 12 (December): 100690.Google Scholar
Kovachy, V. N., Adams, J. N., Tamaresis, J. S., and Feldman, H. M.. 2015. ‘Reading Abilities in School-Aged Preterm Children: A Review and Meta-Analysis’. Developmental Medicine and Child Neurology 57 (5): 410–19.Google Scholar
Kovas, Y., Haworth, C. M. A., Harlaar, N., et al. 2007. ‘Overlap and Specificity of Genetic and Environmental Influences on Mathematics and Reading Disability in 10-Year-Old Twins’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 48 (9): 914–22.Google Scholar
Kovas, Y., Giampietro, V, Viding, E, et al. 2009. ‘Brain Correlates of Non-Symbolic Numerosity Estimation in Low and High Mathematical Ability Children’. PloS One 4 (2): e4587.Google Scholar
Kovas, Y., Claire, M. A. Haworth, P. Dale, S., and Plomin, R. 2007. ‘The Genetic and Environmental Origins of Learning Abilities and Disabilities in the Early School Years’. Monographs of the Society for Research in Child Development 72 (3): vii, 1–144.Google Scholar
Kovas, Y., Haworth, C. M. A., Petrill, S.A., and Plomin, R. 2007. ‘Mathematical Ability of 10-Year-Old Boys and Girls: Genetic and Environmental Etiology of Typical and Low Performance’. Journal of Learning Disabilities 40 (6): 554–67.Google Scholar
Kovas, Y., and Plomin, R. 2006. ‘Generalist Genes: Implications for the Cognitive Sciences’. Trends in Cognitive Sciences 10 (5): 198–203.Google Scholar
Kovelman, I., Norton, E. S., Christodoulou, J. A., et al. 2012. ‘Brain Basis of Phonological Awareness for Spoken Language in Children and Its Disruption in Dyslexia’. Cerebral Cortex 22 (4): 754–64.Google Scholar
Krafnick, A. J., and Evans, T. M.. 2018. ‘Neurobiological Sex Differences in Developmental Dyslexia’. Frontiers in Psychology 9: 2669.Google Scholar
Krafnick, A. J., Flowers, D. L, Luetje, M. M., Napoliello, E. M., and Eden, G. F.. 2014. ‘An Investigation into the Origin of Anatomical Differences in Dyslexia’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 34 (3): 901–8.Google Scholar
Krafnick, A. J., Lynn Flowers, D., Napoliello, E. M., and Eden, G. F.. 2011. ‘Gray Matter Volume Changes Following Reading Intervention in Dyslexic Children’. NeuroImage 57 (3): 733–41.Google Scholar
Kraft, I., Schreiber, J, Cafiero, R, et al. 2016. ‘Predicting Early Signs of Dyslexia at a Preliterate Age by Combining Behavioral Assessment with Structural MRI’. NeuroImage 143 (December): 378–86.Google Scholar
Krajewski, K., and Schneider, W. 2009. ‘Exploring the Impact of Phonological Awareness, Visual-Spatial Working Memory, and Preschool Quantity-Number Competencies on Mathematics Achievement in Elementary School: Findings from a 3-Year Longitudinal Study’. Journal of Experimental Child Psychology 103 (4): 516–31.Google Scholar
Kramer, M. S., Aboud, F, Mironova, E, et al. 2008. ‘Breastfeeding and Child Cognitive Development: New Evidence from a Large Randomized Trial’. Archives of General Psychiatry 65 (5): 578–84.Google Scholar
Krapohl, E., Hannigan, L. J., Pingault, J-B, et al. 2017. ‘Widespread Covariation of Early Environmental Exposures and Trait-Associated Polygenic Variation’. Proceedings of the National Academy of Sciences of the United States of America 114 (44): 11727–32.Google Scholar
Krapohl, E., Rimfeld, K, Shakeshaft, N. G., et al. 2014. ‘The High Heritability of Educational Achievement Reflects Many Genetically Influenced Traits, Not Just Intelligence’. Proceedings of the National Academy of Sciences of the United States of America 111 (42): 15273–8.Google Scholar
Krinzinger, H., Kaufmann, L, Dowker, A, et al. 2007. ‘Deutschsprachige Version Des Fragebogens Für Rechenangst (FRA) Für 6- Bis 9-Jährige Kinder’. Zeitschrift Fur Kinder- Und Jugendpsychiatrie Und Psychotherapie 35 (5): 341–51.Google Scholar
Krinzinger, H., Kaufmann, L, and Willmes, K. 2009. ‘Math Anxiety and Math Ability in Early Primary School Years’. Journal of Psychoeducational Assessment 27 (3): 206–25.Google Scholar
Krinzinger, H., Koten, J. W, Horoufchin, H, et al. 2011. ‘The Role of Finger Representations and Saccades for Number Processing: An FMRI Study in Children’. Frontiers in Psychology 2 (December): 373.Google Scholar
Kristjansson, A. L., Thomas, S, Lilly, C. L., et al. 2018. ‘Maternal Smoking during Pregnancy and Academic Achievement of Offspring over Time: A Registry Data-Based Cohort Study’. Preventive Medicine 113 (August): 74–9.Google Scholar
Krizhevsky, Alex, Sutskever, Ilya, and Hinton, Geoffrey E.. 2017. ‘ImageNet Classification with Deep Convolutional Neural Networks’. Communications of the ACM. https://doi.org/10.1145/3065386.Google Scholar
Krueger, R. F., and Markon, K.E.. 2014. ‘The Role of the DSM-5 Personality Trait Model in Moving toward a Quantitative and Empirically Based Approach to Classifying Personality and Psychopathology’. Annual Review of Clinical Psychology 10: 477–501.Google Scholar
Kubilius, J., Bracci, S, and Op de Beeck, H. P.. 2016. ‘Deep Neural Networks as a Computational Model for Human Shape Sensitivity’. PLoS Computational Biology 12 (4): e1004896.CrossRefGoogle ScholarPubMed
Kubota, E. C., Joo, S. J, Huber, E, and Yeatman, J. D.. 2019. ‘Word Selectivity in High-Level Visual Cortex and Reading Skill’. Developmental Cognitive Neuroscience 36 (September 2018): 100593.Google Scholar
Kucian, K. 2016. ‘Developmental Dyscalculia and the Brain’. In Berch, D, Geary, D, and Mann Koepke, K (eds.), Development of Mathematical Cognition, 165–93. Elsevier.Google Scholar
Kucian, K. 2021. ‘Chapter 10 - Developmental Course of Numerical Learning Problems in Children and How to Prevent Dyscalculia: A Summary of the Longitudinal Examination of Children from Kindergarten to Secondary School’. In W. Fias and A. Henik (eds.), Heterogeneous Contributions to Numerical Cognition, 229–51. Academic Press.Google Scholar
Kucian, K., Ashkenazi, S. S, Hänggi, J, et al. 2014. ‘Developmental Dyscalculia: A Dysconnection Syndrome?’ Brain Structure & Function 219 (5): 1721–33.Google Scholar
Kucian, K., and von Aster, M. 2015. ‘Developmental Dyscalculia’. European Journal of Pediatrics 174 (1): 1–13.Google Scholar
Kucian, K., von Aster, M, Loenneker, T, Dietrich, T, and Martin, E. 2008. ‘Development of Neural Networks for Exact and Approximate Calculation: A FMRI Study’. Developmental Neuropsychology 33 (4): 447–73.Google Scholar
Kucian, K., Loenneker, T, Dietrich, T, et al. 2006. ‘Impaired Neural Networks for Approximate Calculation in Dyscalculic Children: A Functional MRI Study’. Behavioral and Brain Functions: BBF 2 (September): 31.Google Scholar
Kucian, K., Loenneker, T, Martin, E, and von Aster, M. 2011. ‘Non-Symbolic Numerical Distance Effect in Children With and Without Developmental Dyscalculia: A Parametric fMRI Study’. Developmental Neuropsychology 36 (6): 741–62. https://doi.org/10.1080/87565641.2010.549867.CrossRefGoogle ScholarPubMed
Kucian, K., McCaskey, U, O’Gorman Tuura, R, and von Aster, M. 2018. ‘Neurostructural Correlate of Math Anxiety in the Brain of Children’. Translational Psychiatry 8 (1): 273.CrossRefGoogle ScholarPubMed
Kucian, K., Grond, U., Rotzer, S., et al. 2011. ‘Mental Number Line Training in Children with Developmental Dyscalculia’. NeuroImage 57 (3): 782–95.Google Scholar
Kuhl, P. K. 2004. ‘Early Language Acquisition: Cracking the Speech Code’. Nature Reviews. Neuroscience 5 (11): 831–43.Google Scholar
Kuhl, U., Friederici, A. D., LEGASCREEN Consortium, and Skeide, M. A.. 2020a. ‘Early Cortical Surface Plasticity Relates to Basic Mathematical Learning’. NeuroImage 204 (January): 116235.Google Scholar
Kuhl, U., Neef, N. E., Kraft, I., et al. 2020b. ‘The Emergence of Dyslexia in the Developing Brain’. NeuroImage 211 (May): 116633.Google Scholar
Kuhl, U., Sobotta, S., Legascreen Consortium, and M. A. Skeide. (in press) Mathematical learning deficits originate in early childhood from atypical development of a frontoparietal brain network. PLoS Biol. 2021 Sep 30;19(9):e3001407. doi: 10.1371/journal.pbio.3001407.Google Scholar
Kuja-Halkola, R., D’Onofrio, B. M., Larsson, H., and Lichtenstein, P.. 2014. ‘Maternal Smoking during Pregnancy and Adverse Outcomes in Offspring: Genetic and Environmental Sources of Covariance’. Behavior Genetics 44 (5): 456–67.Google Scholar
Kussmaul, A. 1877. Die Storungen Der Sprache [A Disorder of Speech]. FCW Vogel.Google Scholar
Kyttälä, M., and Björn, P. M.. 2010. ‘Prior Mathematics Achievement, Cognitive Appraisals and Anxiety as Predictors of Finnish Students’ Later Mathematics Performance and Career Orientation’. Educational Psychology Review 30 (4): 431–48.Google Scholar
Labouesse, M. A., Langhans, W., and Meyer, U.. 2015. ‘Long-Term Pathological Consequences of Prenatal Infection: Beyond Brain Disorders’. American Journal of Physiology. Regulatory, Integrative and Comparative Physiology 309 (1): R1–12.Google Scholar
Landerl, K., Göbel, S. M., and Moll, K.. 2013. ‘Core Deficit and Individual Manifestations of Developmental Dyscalculia (DD): The Role of Comorbidity’. Trends in Neuroscience and Education 2 (2): 38–42.Google Scholar
Landerl, K. 2013. ‘Development of Numerical Processing in Children with Typical and Dyscalculic Arithmetic Skills – a Longitudinal Study’. Frontiers in Psychology 4: 459.Google Scholar
Landerl, K., Bevan, A., and Butterworth, B.. 2004. ‘Developmental Dyscalculia and Basic Numerical Capacities: A Study of 8-9-Year-Old Students’. Cognition 93 (2): 99–125.Google Scholar
Landerl, K., Fussenegger, B., Moll, K., and Willburger, E.. 2009. ‘Dyslexia and Dyscalculia: Two Learning Disorders with Different Cognitive Profiles’. Journal of Experimental Child Psychology 103 (3): 309–24.Google Scholar
Landerl, K., Freudenthaler, H. H., Heene, M., et al. 2019. ‘Phonological Awareness and Rapid Automatized Naming as Longitudinal Predictors of Reading in Five Alphabetic Orthographies with Varying Degrees of Consistency’. Scientific Studies of Reading 23 (3): 220–34. https://doi.org/10.1080/10888438.2018.1510936.Google Scholar
Landerl, K., and Kölle, C.. 2009. ‘Typical and Atypical Development of Basic Numerical Skills in Elementary School’. Journal of Experimental Child Psychology 103 (4): 546–65.Google Scholar
Landerl, K., and Moll, K.. 2010. ‘Comorbidity of Learning Disorders: Prevalence and Familial Transmission’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 51 (3): 287–94.Google Scholar
Landerl, K., Ramus, F., Moll, K., et al. 2013. ‘Predictors of Developmental Dyslexia in European Orthographies with Varying Complexity’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 54 (6): 686–94.Google Scholar
Landerl, , Vogel, K. S. E., Grabner, R. H., Chapter 15 – Early neurocognitive development of dyscalculia, ed. W. Fias and A. Henik, Heterogeneous Contributions to Numerical Cognition, Academic Press, 2021, pp. 359–82. https://doi.org/10.1016/B978-0-12-817414-2.00011-7.Google Scholar
Landerl, K., and Willburger, E.. 2010. ‘Temporal Processing, Attention, and Learning Disorders’. Learning and Individual Differences 20 (5): 393–401. https://doi.org/10.1016/j.lindif.2010.03.008.Google Scholar
Landerl, K., and Wimmer, H.. 2000. ‘Deficits in Phoneme Segmentation Are Not the Core Problem of Dyslexia: Evidence from German and English Children’. Applied Psycholinguistics 21 (2): 243–62.Google Scholar
Landi, N., Trey, A., Crowley, M. J., Wu, J., and Mayes, L.. 2017. ‘Prenatal Cocaine Exposure Impacts Language and Reading Into Late Adolescence: Behavioral and ERP Evidence’. Developmental Neuropsychology 42 (6): 369–86.Google Scholar
Langer, N., Peysakhovich, B., Zuk, J., et al. 2015. ‘White Matter Alterations in Infants at Risk for Developmental Dyslexia’. Cerebral Cortex 27 (2), 1027–36.Google Scholar
Lange, S., Probst, C., Rehm, J., and Popova, S.. 2018. ‘National, Regional, and Global Prevalence of Smoking during Pregnancy in the General Population: A Systematic Review and Meta-Analysis’. The Lancet: Global Health 6 (7): e769–76.Google Scholar
Lanphear, B. P., Hornung, R., Khoury, J., et al. 2005. ‘Low-Level Environmental Lead Exposure and Children’s Intellectual Function: An International Pooled Analysis’. Environmental Health Perspectives 113 (7). https://doi.org/10.1289/ehp.7688.Google Scholar
Lauermann, F., Eccles, J. S., and Pekrun, R.. 2017. ‘Why Do Children Worry about Their Academic Achievement? An Expectancy-Value Perspective on Elementary Students’ Worries about Their Mathematics and Reading Performance’. ZDM: The International Journal on Mathematics Education 49 (3): 339–54.Google Scholar
Lauritzen, L., Hansen, H. S., Jørgensen, M. H., and Michaelsen, K. F.. 2001. ‘The Essentiality of Long Chain N-3 Fatty Acids in Relation to Development and Function of the Brain and Retina’. Progress in Lipid Research 40 (1–2): 1–94.Google Scholar
Law, J., Charlton, J, Dockrell, J, et al. 2017. ‘Early Language Development: Needs, Provision, and Intervention for Preschool Children from Socio-Economically Disadvantage Backgrounds: A Report for the Education Endowment Foundation: October 2017’. www.research.manchester.ac.uk/portal/en/publications/early-language-development-needs-provision-and-intervention-for-preschool-children-from-socioeconomically-disadvantage-backgrounds(2429d543-cb90-4381-bf9b-6e83f06991f5)/export.html.Google Scholar
Lawton, T. 2016. ‘Improving Dorsal Stream Function in Dyslexics by Training Figure/Ground Motion Discrimination Improves Attention, Reading Fluency, and Working Memory’. Frontiers in Human Neuroscience 10 (August): 397.Google Scholar
Lebel, C., Benischek, A, Geeraert, B, et al. 2019. ‘Developmental Trajectories of White Matter Structure in Children with and without Reading Impairments’. Developmental Cognitive Neuroscience 36 (April): 100633.Google Scholar
Lebel, C., Walker, L., Leemans, A., Phillips, L., and Beaulieu, C.. 2008. ‘Microstructural Maturation of the Human Brain from Childhood to Adulthood’. NeuroImage 40 (3): 1044–55.Google Scholar
Lee, S. J., Woodward, L. J., and Henderson, J. M. T.. 2019. ‘Educational Achievement at Age 9.5 Years of Children Born to Mothers Maintained on Methadone during Pregnancy’. PloS One 14 (10): e0223685.Google Scholar
Lehongre, K., Ramus, F, Villiermet, N, Schwartz, D, and Giraud, A.-L. 2011. ‘Altered Low-γ Sampling in Auditory Cortex Accounts for the Three Main Facets of Dyslexia’. Neuron 72 (6): 1080–90.Google Scholar
Leiss, D. (2007). ‘Hilf mir es selbst zu tun’. Lehrerinterventionen beim mathematischen Modellieren. Franzbecker.Google Scholar
Leng, Y. and Wei., Y. 1994. Zhonghua zihai [China’s sea of characters]. Beijing, China: Zhongguo youyi chuban gongsi.Google Scholar
Leong, V., and Goswami, U. 2015. ‘Acoustic-Emergent Phonology in the Amplitude Envelope of Child-Directed Speech’. PloS One 10 (12): e0144411.Google Scholar
Leong, V., Kalashnikova, M, Burnham, D, and Goswami, U. 2017. ‘The Temporal Modulation Structure of Infant-Directed Speech’. Open Mind 1 (2): 78–90.Google Scholar
Leong, V., Stone, M. A., Turner, R. E., and Goswami, U. 2014. ‘A Role for Amplitude Modulation Phase Relationships in Speech Rhythm Perception’. The Journal of the Acoustical Society of America 136 (1): 366–81.Google Scholar
Leppänen, P. H. T., Hämäläinen, J. A, Salminen, H. K, et al. 2010. ‘Newborn Brain Event-Related Potentials Revealing Atypical Processing of Sound Frequency and the Subsequent Association with Later Literacy Skills in Children with Familial Dyslexia’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 46 (10): 1362–76.Google Scholar
Levy, L. M., Reis, I. L., and Grafman, J.. 1999. ‘Metabolic Abnormalities Detected by 1H-MRS in Dyscalculia and Dysgraphia’. Neurology 53 (3): 639–41.Google Scholar
Liang, H., Vuong, A. M., Xie, C, et al. 2019. ‘Childhood Polybrominated Diphenyl Ether (PBDE) Serum Concentration and Reading Ability at Ages 5 and 8 Years: The HOME Study’. Environment International 122 (January): 330–9.Google Scholar
Libertus, M. E., Feigenson, L, and Halberda, J. 2011. ‘Preschool Acuity of the Approximate Number System Correlates with School Math Ability’. Developmental Science 14 (6): 1292–1300.Google Scholar
Liebig, J., Friederici, A. D., Neef, N. E., and LEGASCREEN Consortium. 2020. ‘TEMPORARY REMOVAL: Auditory Brainstem Measures and Genotyping Boost the Prediction of Literacy: A Longitudinal Study on Early Markers of Dyslexia’. Developmental Cognitive Neuroscience 46 (December): 100869.Google Scholar
Li, J., Robinson, M, Malacova, E, et al. 2013. ‘Maternal Life Stress Events in Pregnancy Link to Children’s School Achievement at Age 10 Years’. The Journal of Pediatrics 162 (3): 483–9.Google Scholar
Li, J., Na, L., Ma, H., et al. 2015. ‘Multigenerational Effects of Parental Prenatal Exposure to Famine on Adult Offspring Cognitive Function’. Scientific Reports 5 (September): 13792.Google Scholar
Lillicrap, T. P., Santoro, A, Marris, L, Akerman, C.J., and Hinton, G. 2020. ‘Backpropagation and the Brain’. Nature Reviews: Neuroscience 21 (6): 335–46.Google Scholar
Limperopoulos, C., Bassan, H, Gauvreau, K, et al. 2007. ‘Does Cerebellar Injury in Premature Infants Contribute to the High Prevalence of Long-Term Cognitive, Learning, and Behavioral Disability in Survivors?’ Pediatrics 120 (3): 584–93.Google Scholar
Linkersdörfer, J., Jurcoane, A, Lindberg, S, et al. 2015. ‘The Association between Gray Matter Volume and Reading Proficiency: A Longitudinal Study of Beginning Readers’. Journal of Cognitive Neuroscience 27 (2): 308–18.Google Scholar
Linkersdörfer, J., Lonnemann, J, Lindberg, S, Hasselhorn, M, and Fiebach, C. J.. 2012. ‘Grey Matter Alterations Co-Localize with Functional Abnormalities in Developmental Dyslexia: An ALE Meta-Analysis’. PloS One 7 (8): e43122.Google Scholar
Liu, L., Wang, J, Shao, S, et al. 2016. ‘Descriptive Epidemiology of Prenatal and Perinatal Risk Factors in a Chinese Population with Reading Disorder’. Scientific Reports 6 (November): 36697.Google Scholar
Li, Y., Chen, F, and Huang, W. 2016. ‘Neural Plasticity Following Abacus Training in Humans: A Review and Future Directions’. Neural Plasticity 2016 (January): 1213723.Google Scholar
Li, Y., Hu, Y., Zhao, M., et al. 2013. ‘The Neural Pathway Underlying a Numerical Working Memory Task in Abacus-Trained Children and Associated Functional Connectivity in the Resting Brain’. Brain Research 1539 (November): 24–33.Google Scholar
Li, Y., Wang, Y, Hu, Y, Liang, Y, and Chen, F. 2013. ‘Structural Changes in Left Fusiform Areas and Associated Fiber Connections in Children with Abacus Training: Evidence from Morphometry and Tractography’. Frontiers in Human Neuroscience 7 (July): 335.Google Scholar
Lizarazu, M., Lallier, M, Molinaro, N, et al. 2015. ‘Developmental Evaluation of Atypical Auditory Sampling in Dyslexia: Functional and Structural Evidence’. Human Brain Mapping 36 (12): 4986–5002.Google Scholar
Lizarazu, M., Scotto di Covella, L., van Wassenhove, V., et al. 2021. ‘Neural Entrainment to Speech and Nonspeech in Dyslexia: Conceptual Replication and Extension of Previous Investigations’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 137 (April): 160–78.Google Scholar
Li, Z., Ma, X, Peltier, S, et al. 2008. ‘Occipital-Temporal Reduction and Sustained Visual Attention Deficit in Prenatal Alcohol Exposed Adults’. Brain Imaging and Behavior 2 (1): 39–48.Google Scholar
Lohvansuu, K., Hämäläinen, J. A., Ervast, L., Lyytinen, H, and Leppänen, P. H. T.. 2018. ‘Longitudinal Interactions between Brain and Cognitive Measures on Reading Development from 6 Months to 14 Years’. Neuropsychologia 108 (January): 6–12.Google Scholar
Low, J. A., Galbraith, R. S., Muir, D. W., et al. 1988. ‘Motor and Cognitive Deficits after Intrapartum Asphyxia in the Mature Fetus’. American Journal of Obstetrics and Gynecology 158 (2): 356–61.Google Scholar
Lozano, J., García-Algar, O, Marchei, E, et al. 2007. ‘Prevalence of Gestational Exposure to Cannabis in a Mediterranean City by Meconium Analysis’. Acta Paediatrica 96 (12): 1734–7.Google Scholar
Lubman, D. I., Cheetham, A, and Yücel, M. 2015. ‘Cannabis and Adolescent Brain Development’. Pharmacology & Therapeutics 148 (April): 1–16.Google Scholar
Ludwig, K. U., Sämann, P., Alexander, M., et al. 2013. ‘A Common Variant in Myosin-18B Contributes to Mathematical Abilities in Children with Dyslexia and Intraparietal Sulcus Variability in Adults’. Translational Psychiatry 3 (February): e229.Google Scholar
Łuniewska, M., Chyl, K, Dębska, A, et al. 2019. ‘Children With Dyslexia and Familial Risk for Dyslexia Present Atypical Development of the Neuronal Phonological Network’. Frontiers in Neuroscience 13 (November): 1287.Google Scholar
Łuniewska, M., Chyl, K, Dębska, A, et al. 2018. ‘Neither Action nor Phonological Video Games Make Dyslexic Children Read Better’. Scientific Reports 8 (1): 549.Google Scholar
Lutchmaya, S., Baron-Cohen, S, and Raggatt, P. 2001. ‘Foetal Testosterone and Vocabulary Size in 18- and 24-Month-Old Infants’. Infant Behavior & Development 24 (4): 418–24.Google Scholar
Lyon, G. R., Shaywitz, S. E., and Shaywitz, B. A.. 2003. ‘A Definition of Dyslexia’. Annals of Dyslexia 53 (1): 1–14.CrossRefGoogle Scholar
Lyons, I. M., Ansari, D, and Beilock, S. L.. 2012. ‘Symbolic Estrangement: Evidence against a Strong Association between Numerical Symbols and the Quantities They Represent’. Journal of Experimental Psychology: General 141 (4): 635–41. https://doi.org/10.1037/a0027248.Google Scholar
Lyons, I. M., Price, G. R., Vaessen, A, Blomert, L, and Ansari, D. 2014. ‘Numerical Predictors of Arithmetic Success in Grades 1-6’. Developmental Science 17 (5): 714–26.Google Scholar
Lyons, I. M., Vogel, S. E., and Ansari, D.. 2016. ‘On the Ordinality of Numbers: A Review of Neural and Behavioral Studies’. Progress in Brain Research 227 (May): 187–221.Google Scholar
Maher, B. 2008. ‘Personal Genomes: The Case of the Missing Heritability’. Nature 456 (7218): 18–21.Google Scholar
Maisog, J. M., Einbinder, E. R., Flowers, D. L., Turkeltaub, P. E, and Eden, G. F.. 2008. ‘A Meta-Analysis of Functional Neuroimaging Studies of Dyslexia’. Annals of the New York Academy of Sciences 1145 (December): 237–59.Google Scholar
Majerus, S. 2019. ‘Verbal Working Memory and the Phonological Buffer: The Question of Serial Order’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 112 (March): 122–33.Google Scholar
Mak, L. E., Croy, B. A, Kay, V, et al. 2018. ‘Resting-State Functional Connectivity in Children Born from Gestations Complicated by Preeclampsia: A Pilot Study Cohort’. Pregnancy Hypertension 12 (April): 23–8.Google Scholar
Makrides, M., Neumann, M. A., Byard, R. W., Simmer, K., and Gibson, R. A.. 1994. ‘Fatty Acid Composition of Brain, Retina, and Erythrocytes in Breast- and Formula-Fed Infants’. The American Journal of Clinical Nutrition 60 (2): 189–94.Google Scholar
Malanchini, M., Engelhardt, L. E., Grotzinger, A. D., Paige Harden, K., and Tucker-Drob, E. M.. 2019. ‘“Same but Different”: Associations between Multiple Aspects of Self-Regulation, Cognition, and Academic Abilities’. Journal of Personality and Social Psychology 117 (6): 1164–88.Google Scholar
Malanchini, M., Rimfeld, K, Allegrini, A. G., Ritchie, S. J., and Plomin, R.. 2020. ‘Cognitive Ability and Education: How Behavioural Genetic Research Has Advanced Our Knowledge and Understanding of Their Association’. Neuroscience and Biobehavioral Reviews 111 (April): 229–45.Google Scholar
Malanchini, M., Rimfeld, K, Wang, Z et al. 2020. ‘Genetic Factors Underlie the Association between Anxiety, Attitudes and Performance in Mathematics’. Translational Psychiatry 10 (1): 12.Google Scholar
Malanchini, M., Wang, Z, Voronin, I, et al. 2017. ‘Reading Self-Perceived Ability, Enjoyment and Achievement: A Genetically Informative Study of Their Reciprocal Links over Time’. Developmental Psychology 53 (4): 698–712.Google Scholar
Malisza, K. L., Allman, A.-A, Shiloff, D.H, et al. 2005. ‘Evaluation of Spatial Working Memory Function in Children and Adults with Fetal Alcohol Spectrum Disorders: A Functional Magnetic Resonance Imaging Study’. Pediatric Research 58 (6): 1150–7.Google Scholar
Maloney, E. A., Ramirez, G, Gunderson, E. A., Levine, S. C., and Beilock, S. L.. 2015. ‘Intergenerational Effects of Parents’ Math Anxiety on Children’s Math Achievement and Anxiety’. Psychological Science 26 (9): 1480–8.Google Scholar
Maloney, E. A., Schaeffer, M. W., and Beilock, S. L.. 2013. ‘Mathematics Anxiety and Stereotype Threat: Shared Mechanisms, Negative Consequences and Promising Interventions’. Research in Mathematics Education 15 (2): 115–28.Google Scholar
Mammarella, I. C., Caviola, S, and Dowker, A. 2019. Mathematics Anxiety: What Is Known and What Is Still to Be Understood. Routledge, Taylor & Francis Group.Google Scholar
Mammarella, I. C., Caviola, S, Giofrè, D, and Szűcs, D. 2018. ‘The Underlying Structure of Visuospatial Working Memory in Children with Mathematical Learning Disability’. The British Journal of Developmental Psychology 36 (2): 220–35.Google Scholar
Mammarella, I. C., Hill, F, Devine, A, Caviola, S, and Szűcs, D. 2015. ‘Math Anxiety and Developmental Dyscalculia: A Study on Working Memory Processes’. Journal of Clinical and Experimental Neuropsychology 37 (8): 878–87.Google Scholar
Mañeru, C., Serra-Grabulosa, J. M., Junqué, C, et al. 2003. ‘Residual Hippocampal Atrophy in Asphyxiated Term Neonates’. Journal of Neuroimaging: Official Journal of the American Society of Neuroimaging 13 (1): 68–74.Google Scholar
Manis, F. R., Seidenberg, M. S., Doi, L. M., McBride-Chang, C, and Petersen, A. 1996. ‘On the Bases of Two Subtypes of Development Dyslexia’. Cognition 58 (2): 157–95. https://doi.org/10.1016/0010-0277(95)00679-6.Google Scholar
Manolio, T. A., Collins, F. S., Cox, N. J., et al. 2009. ‘Finding the Missing Heritability of Complex Diseases’. Nature 461 (7265): 747–53.Google Scholar
Manolitsis, G., and Georgiou, G. K.. 2015. ‘The Cognitive Profiles of Poor Readers/Good Spellers and Good Readers/Poor Spellers in a Consistent Orthography: A Retrospective Analysis’. Preschool and Primary Education 3 (2): 103. https://doi.org/10.12681/ppej.178.Google Scholar
Marcus, G. F. 2003. The Algebraic Mind: Integrating Connectionism and Cognitive Science. MIT Press.Google Scholar
Mareschal, D., and Thomas, M. S. C.. 2007. ‘Computational Modeling in Developmental Psychology’. IEEE Transactions on Evolutionary Computation 11 (2): 137–50.Google Scholar
Marino, C., Scifo, P, Rosa, P. A. Della, et al. 2014. ‘The DCDC2/intron 2 Deletion and White Matter Disorganization: Focus on Developmental Dyslexia’. Cortex 57: 227–243. https://doi.org/10.1016/j.cortex.2014.04.016.Google Scholar
Markowitz, G. 2018. ‘From Industrial Toxins to Worldwide Pollutants: A Brief History of Polychlorinated Biphenyls’. Public Health Reports 133 (6): 721–5.Google Scholar
Marks, R. A., Kovelman, I, Kepinska, O, et al. 2019. ‘Spoken Language Proficiency Predicts Print-Speech Convergence in Beginning Readers’. NeuroImage 201 (November): 116021.Google Scholar
Martin, A., Kronbichler, M, and Richlan, F. 2016. ‘Dyslexic Brain Activation Abnormalities in Deep and Shallow Orthographies: A Meta‐analysis of 28 Functional Neuroimaging Studies’. Human Brain Mapping 37 (7): 2676–99. https://doi.org/10.1002/hbm.23202.Google Scholar
Martin, M. M., Graham, D.L., McCarthy, D. M., Bhide, P. G., and Stanwood, G. D.. 2016. ‘Cocaine-Induced Neurodevelopmental Deficits and Underlying Mechanisms’. Birth Defects Research. Part C, Embryo Today: Reviews 108 (2): 147–73.Google Scholar
Martin, N., Boomsma, D., and Machin, G.. 1997. ‘A Twin-Pronged Attack on Complex Traits’. Nature Genetics 17 (4): 387–92.CrossRefGoogle ScholarPubMed
Martin, N. G., and Eaves, L. J.. 1977. ‘Stages: The First to Determine the Genetical and Environmental Model’. Most 38: 79–95.Google Scholar
Martín-Puga, M. E., J. Justicia-Galiano, M., Mar Gómez-Pérez, M., and Pelegrina, S.. 2020. ‘Psychometric Properties, Factor Structure, and Gender and Educational Level Invariance of the Abbreviated Math Anxiety Scale (AMAS) in Spanish Children and Adolescents’. Assessment 29 (3): 425–40.Google Scholar
Mascheretti, S., De Luca, A., Trezzi, V., et al. 2017. ‘Neurogenetics of Developmental Dyslexia: From Genes to Behavior through Brain Neuroimaging and Cognitive and Sensorial Mechanisms’. Translational Psychiatry 7: e987. https://doi.org/10.1038/tp.2016.240.Google Scholar
Mason, L. H., Harp, J. P., and Han, D. Y.. 2014. ‘Pb Neurotoxicity: Neuropsychological Effects of Lead Toxicity’. BioMed Research International 2014 (January): 840547.Google Scholar
Matas-Blanco, C., and Caparros-Gonzalez, R. A.. 2020. ‘Influence of Maternal Stress during Pregnancy on Child’s Neurodevelopment’. Psych 2 (4): 186–97.Google Scholar
Matejko, A. A., and Ansari, D. 2015. ‘Drawing Connections between White Matter and Numerical and Mathematical Cognition: A Literature Review’. Neuroscience and Biobehavioral Reviews 48 (January): 35–52.Google Scholar
Matejko, A. A., and Ansari, D 2019. ‘The Neural Association between Arithmetic and Basic Numerical Processing Depends on Arithmetic Problem Size and Not Chronological Age’. Developmental Cognitive Neuroscience 37 (June): 100653.Google Scholar
Matejko, A. A., Hutchison, J. E., and Ansari, D. 2019. ‘Developmental Specialization of the Left Intraparietal Sulcus for Symbolic Ordinal Processing’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 114 (May): 41–53.Google Scholar
Matejko, A. A., Price, G. R., Mazzocco, M. M. M., and Ansari, D. 2013. ‘Individual Differences in Left Parietal White Matter Predict Math Scores on the Preliminary Scholastic Aptitude Test’. NeuroImage 66 (February): 604–10.Google Scholar
Mattson, S. N., Bernes, G. A., and Doyle, L. R.. 2019. ‘Fetal Alcohol Spectrum Disorders: A Review of the Neurobehavioral Deficits Associated with Prenatal Alcohol Exposure’. Alcoholism, Clinical and Experimental Research 43 (6): 1046–62.Google Scholar
Matuszewski, Jacek, Kossowski, Bartosz, Bola, Łukasz, et al. 2020. ‘Brain Plasticity Dynamics during Tactile Braille Learning in Sighted Subjects: Multi-Contrast MRI Approach’. NeuroImage 227: 117613.Google Scholar
Maurer, Urs, Blau, Vera C., Yoncheva, Yuliya N., and McCandliss, Bruce D.. 2010. ‘Development of Visual Expertise for Reading: Rapid Emergence of Visual Familiarity for an Artificial Script’. Developmental Neuropsychology 35 (4): 404–22.Google Scholar
Maurer, U., Brem, S., Bucher, K., et al. 2007. Impaired Tuning of a Fast Occipito-Temporal Response for Print in Dyslexic Children Learning to Read. Brain 130 (12): 3200–10. https://doi.org/10.1093/brain/awm193.Google Scholar
Maurer, U., Brem, S, Bucher, K, and Brandeis, D. 2005. ‘Emerging Neurophysiological Specialization for Letter Strings’. Journal of Cognitive Neuroscience 17 (10): 1532–52.Google Scholar
Maurer, U., Brem, S, Kranz, F, et al. 2006. ‘Coarse Neural Tuning for Print Peaks When Children Learn to Read’. NeuroImage 33 (2): 749–58.Google Scholar
Maurer, U., Bucher, K, Brem, S., et al. 2009. ‘Neurophysiology in Preschool Improves Behavioral Prediction of Reading Ability Throughout Primary School’. Biological Psychiatry 66 (4): P341–8. https://doi.org/10.1016/j.biopsych.2009.02.031.Google Scholar
Maurer, U., Schulz, E, Brem, S, et al. 2011. ‘The Development of Print Tuning in Children with Dyslexia: Evidence from Longitudinal ERP Data Supported by fMRI’. NeuroImage 57 (3): 714–22.CrossRefGoogle ScholarPubMed
Ma, X. 1999. ‘A Meta-Analysis of the Relationship between Anxiety toward Mathematics and Achievement in Mathematics’. Journal for Research in Mathematics Education 30 (5): 520–40.Google Scholar
Ma, X., and Xu., J. 2004. ‘The Causal Ordering of Mathematics Anxiety and Mathematics Achievement: A Longitudinal Panel Analysis’. Journal of Adolescence 27 (2): 165–79.Google Scholar
Mazzocco, M. M. M., Feigenson, L, and Halberda, J. 2011. ‘Impaired Acuity of the Approximate Number System Underlies Mathematical Learning Disability (Dyscalculia)’. Child Development 82 (4): 1224–37.Google Scholar
Mazzocco, M. M. M., and Myers, G. F.. 2003. ‘Complexities in Identifying and Defining Mathematics Learning Disability in the Primary School-Age Years’. Annals of Dyslexia 53 (1): 218–53.Google Scholar
McBryde, M., Fitzallen, G. C., Liley, H. G., Taylor, H. G, and Bora, S. 2020. ‘Academic Outcomes of School-Aged Children Born Preterm: A Systematic Review and Meta-Analysis’. JAMA Network Open 3 (4): e202027.Google Scholar
McCandliss, B. D., Cohen, L., and Dehaene, S.. 2003. ‘The Visual Word Form Area: Expertise for Reading in the Fusiform Gyrus’. Trends in Cognitive Sciences 7 (7): 293–9.Google Scholar
McCaskey, U., von Aster, M, Maurer, U., et al. (2018). ‘Longitudinal Brain Development of Numerical Skills in Typically Developing Children and Children with Developmental Dyscalculia’. Frontiers in Human Neuroscience 11, 629.Google Scholar
McCaskey, U., von Aster, M, O’Gorman, R, and Kucian, K. 2020. ‘Persistent Differences in Brain Structure in Developmental Dyscalculia: A Longitudinal Morphometry Study’. Frontiers in Human Neuroscience 14 (July): 272.Google Scholar
McClelland, J. L. 2009. ‘The Place of Modeling in Cognitive Science’. Topics in Cognitive Science 1 (1): 11–38.Google Scholar
McClelland, J. L., and Rumelhart, D. E.. 1981. ‘An Interactive Activation Model of Context Effects in Letter Perception: I. An Account of Basic Findings’. Psychological Review 88 (5): 375–407.Google Scholar
McCloskey, M., and Lindemann, A. M. 1992. ‘MATHNET: Preliminary Results from a Distributed Model of Arithmetic Fact Retrieval’. The Nature and Origins of Mathematical Skills. 569: 365–409.Google Scholar
McCoy, A. R., and Reynolds., A. J. 1998. ‘Evaluating Implementation’. In A. J. Reynolds and H. J. Walberg (eEds.), Advances in Educational Productivity, 117–33. JAI Press.Google Scholar
McCrory, C., and Layte, R. 2011. ‘The Effect of Breastfeeding on Children’s Educational Test Scores at Nine Years of Age: Results of an Irish Cohort Study’. Social Science & Medicine 72 (9): 1515–21.Google Scholar
McGaugh, J. L., Cahill, L., and Roozendaal, B.. 1996. ‘Involvement of the Amygdala in Memory Storage: Interaction with Other Brain Systems’. Proceedings of the National Academy of Sciences of the United States of America 93 (24): 13508–14.Google Scholar
McGrath, L. M., Peterson, R. L., and Pennington, B. F.. 2020. ‘The Multiple Deficit Model: Progress, Problems, and Prospects’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 24 (1): 7–13.Google Scholar
McKenzie, I. A., Ohayon, D., Li, H., et al. 2014. ‘Motor Skill Learning Requires Active Central Myelination’. Science 346 (6207): 318–22.Google Scholar
Meda, S. A., Gelernter, J, Gruen, J. R., et al. 2008. ‘Polymorphism of DCDC2 Reveals Differences in Cortical Morphology of Healthy Individuals – A Preliminary Voxel Based Morphometry Study’. Brain Imaging and Behavior 2: 21–6. https://doi.org/10.1007/s11682-007-9012-1.Google Scholar
Meintjes, E. M., Jacobson, J. L., Molteno, C. D., et al. 2010. ‘An FMRI Study of Number Processing in Children with Fetal Alcohol Syndrome’. Alcoholism, Clinical and Experimental Research 34 (8): 1450–64.Google Scholar
Melby-Lervåg, M., Lyster, S. A. H., and Hulme, C.. 2012. ‘Phonological Skills and Their Role in Learning to Read: A Meta-Analytic Review’. Psychological Bulletin 138 (2): 322–52.Google Scholar
Menghini, D., Finzi, A., Benassi, M., et al. 2010. ‘Different Underlying Neurocognitive Deficits in Developmental Dyslexia: A Comparative Study’. Neuropsychologia 48 (4): 863–72.Google Scholar
Menon, V. 2016. ‘Memory and Cognitive Control Circuits in Mathematical Cognition and Learning’. Progress in Brain Research 227 (June): 159–86.Google Scholar
Menon, V. 2015. ‘Arithmetic in the Child and Adult Brain’. The Oxford Handbook of Numerical Cognition, edited by Cohen, K Kadosh, A. Dowker, , 502–30. . Oxford University Press.Google Scholar
Menon, V., Padmanabhan, A., and Schwartz, F.. 2020. ‘Cognitive Neuroscience of Dyscalculia and Math Learning Disabilities’. In The Oxford Handbook of Developmental Cognitive Neuroscience, edited by Cohen, K Kadosh, . Oxford University Press.Google Scholar
Mensch, S., Baraban, M, Almeida, R., et al. 2015. ‘Synaptic Vesicle Release Regulates Myelin Sheath Number of Individual Oligodendrocytes in Vivo’. Nature Neuroscience 18 (5): 628–30.Google Scholar
Micalizzi, L., Marceau, K., Evans, A. S., et al. 2021. ‘A Sibling-Comparison Study of Smoking during Pregnancy and Risk for Reading-Related Problems’. Neurotoxicology and Teratology 84 (March): 106961.Google Scholar
Michels, L., O’Gorman, R., and Kucian, K.. 2018. ‘Functional Hyperconnectivity Vanishes in Children with Developmental Dyscalculia after Numerical Intervention’. Developmental Cognitive Neuroscience 30 (April): 291–303.Google Scholar
Miller, E. C., Zhang, L., Dummer, B. W., et al. 2012. ‘Differential Modulation of Drug-Induced Structural and Functional Plasticity of Dendritic Spines’. Molecular Pharmacology 82 (2): 333–43.Google Scholar
Miller, S. P., Ramaswamy, V., Michelson, D., et al. 2005. ‘Patterns of Brain Injury in Term Neonatal Encephalopathy’. The Journal of Pediatrics 146 (4): 453–60.Google Scholar
Mills, K. L., Goddings, A.-L., Herting, M. M., et al. 2016. ‘Structural Brain Development between Childhood and Adulthood: Convergence across Four Longitudinal Samples’. NeuroImage 141 (November): 273–81.Google Scholar
Missall, K. N., Mercer, S. H., Martínez, R. S., and Casebeer, D.. 2012. ‘Concurrent and Longitudinal Patterns and Trends in Performance on Early Numeracy Curriculum-Based Measures in Kindergarten Through Third Grade’. Assessment for Effective Intervention: Official Journal of the Council for Educational Diagnostic Services 37 (2): 95–106.Google Scholar
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., and Wager, T. D.. 2000. ‘The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis’. Cognitive Psychology 41 (1): 49–100.Google Scholar
Molfese, D. L. 2000. ‘Predicting Dyslexia at 8 Years of Age Using Neonatal Brain Responses’. Brain and Language 72 (3): 238–45.Google Scholar
Molinaro, N., Lizarazu, M., Lallier, M., Bourguignon, M., and Carreiras, M.. 2016. ‘Out-of-Synchrony Speech Entrainment in Developmental Dyslexia’. Human Brain Mapping 37 (8): 2767–83.Google Scholar
Moll, K., Fussenegger, B., Willburger, E., and Landerl, K.. 2009. ‘RAN Is Not a Measure of Orthographic Processing. Evidence From the Asymmetric German Orthography’. Scientific Studies of Reading 13 (1): 1–25. https://doi.org/10.1080/10888430802631684.Google Scholar
Moll, K., Göbel, S. M., Gooch, D., Landerl, K., and Snowling, M. J.. 2016a. ‘Cognitive Risk Factors for Specific Learning Disorder’. Journal of Learning Disabilities 49 (3): 272–81. https://doi.org/10.1177/0022219414547221.Google Scholar
Moll, K., Göbel, S. M., Gooch, D., Landerl, K., and Snowling, M. J. 2016b. ‘Cognitive Risk Factors for Specific Learning Disorder: Processing Speed, Temporal Processing, and Working Memory’. Journal of Learning Disabilities 49 (3): 272–81.Google Scholar
Moll, K., Göbel, S. M., and Snowling, M. J.. 2015. ‘Basic Number Processing in Children with Specific Learning Disorders: Comorbidity of Reading and Mathematics Disorders’. Child Neuropsychology: A Journal on Normal and Abnormal Development in Childhood and Adolescence 21 (3): 399–417.Google Scholar
Moll, K., Kunze, S., Neuhoff, N., Bruder, J., and Schulte-Körne, G.. 2014. ‘Specific Learning Disorder: Prevalence and Gender Differences’. PloS One 9 (7): e103537.Google Scholar
Moll, K., and Landerl, K.. 2009. ‘Double Dissociation between Reading and Spelling Deficits’. Scientific Studies of Reading 13 (5): 359–82. https://doi.org/10.1080/10888430903162878.Google Scholar
Moll, K., Landerl, K., Snowling, M. J., and Schulte-Körne, G.. 2019. ‘Understanding Comorbidity of Learning Disorders: Task-Dependent Estimates of Prevalence’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 60 (3): 286–94.Google Scholar
Moll, K., Ramus, F., Bartling, J., et al. 2014. ‘Cognitive Mechanisms Underlying Reading and Spelling Development in Five European Orthographies’. Learning and Instruction 29: 65–77. https://doi.org/10.1016/j.learninstruc.2013.09.003.Google Scholar
Monnelly, V. J., Anblagan, D., Quigley, A., et al. 2018. ‘Prenatal Methadone Exposure Is Associated with Altered Neonatal Brain Development’. NeuroImage. Clinical 18: 9–14.Google Scholar
Monzalvo, K., Fluss, J., Billard, C., Dehaene, S., and Dehaene-Lambertz, G.. 2012. ‘Cortical Networks for Vision and Language in Dyslexic and Normal Children of Variable Socio-Economic Status’. NeuroImage 61 (1): 258–74.Google Scholar
Moore, E. M., Migliorini, R., Infante, M. A., and Riley, E. P.. 2014. ‘Fetal Alcohol Spectrum Disorders: Recent Neuroimaging Findings’. Current Developmental Disorders Reports 1 (3): 161–72.Google Scholar
Moreau, D., Wiebels, K., Wilson, A. J., and Waldie, K. E.. 2019. ‘Volumetric and Surface Characteristics of Gray Matter in Adult Dyslexia and Dyscalculia’. Neuropsychologia 127 (April): 204–10.Google Scholar
Morie, K. P., Crowley, M. J., Mayes, L. C., and Potenza, M. N.. 2019. ‘Prenatal Drug Exposure from Infancy through Emerging Adulthood: Results from Neuroimaging’. Drug and Alcohol Dependence 198 (May): 39–53.Google Scholar
Morken, F., Helland, T., Hugdahl, K., and Specht, K.. 2017. ‘Reading in Dyslexia across Literacy Development: A Longitudinal Study of Effective Connectivity’. NeuroImage 144 (Pt A): 92–100.Google Scholar
Morsanyi, K., van Bers, B. M. C. W., O’Connor, P. A., and McCormack, T.. 2018. ‘Developmental Dyscalculia Is Characterized by Order Processing Deficits: Evidence from Numerical and Non-Numerical Ordering Tasks’. Developmental Neuropsychology 43 (7): 595–621.Google Scholar
Moulton, E., Bouhali, F., Monzalvo, K., et al. 2019. ‘Connectivity between the Visual Word Form Area and the Parietal Lobe Improves after the First Year of Reading Instruction: A Longitudinal MRI Study in Children’. Brain Structure & Function 224 (4): 1519–36.Google Scholar
Mount, C. W., and Monje, M.. 2017. ‘Wrapped to Adapt: Experience-Dependent Myelination’. Neuron 95 (4): 743–56.Google Scholar
Moura, R., Wood, G., Pinheiro-Chagas, P., et al. 2013. ‘Transcoding Abilities in Typical and Atypical Mathematics Achievers: The Role of Working Memory and Procedural and Lexical Competencies’. Journal of Experimental Child Psychology 116 (3): 707–27.Google Scholar
Moura, R., Lopes-Silva, J. B., and Vieira, L. R.. 2015. ‘From ‘five’ to 5 for 5 Minutes: Arabic Number Transcoding as a Short, Specific, and Sensitive Screening Tool for Mathematics Learning Difficulties’. Archives of Clinical Neuropsychology 30 (1): 88–98. https://doi.org/10.1093/arclin/acu071.Google Scholar
Moyer, R. S., and Landauer, T. K.. 1967. ‘Time Required for Judgements of Numerical Inequality’. Nature 215 (5109): 1519–20.Google Scholar
Mullen, K. M., Vohr, B. R., Katz, K. H., et al. 2011. ‘Preterm Birth Results in Alterations in Neural Connectivity at Age 16 Years’. NeuroImage 54 (4): 2563–70.Google Scholar
Mullis, I. V. S., Martin, M. O., Foy, P., Kelly, D. l., and Fishbein, B.. 2020. TIMSS 2019 International Results in Mathematics and Science. https://timss2019.org/reports/wp-content/themes/timssandpirls/download-center/TIMSS-2019-International-Results-in-Mathematics-and-Science.pdfGoogle Scholar
Murray, L., Arteche, A., Fearon, P., et al. 2010. ‘The Effects of Maternal Postnatal Depression and Child Sex on Academic Performance at Age 16 Years: A Developmental Approach’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 51 (10): 1150–9.Google Scholar
Murphy, J. 1973. ‘The Education Bureaucracies Implement Novel Policy: The Politics of Title I of ESEA’. In Allan Sindler (ed.), Policy and Politics in America, 160–99. Little, Brown.Google Scholar
Mushak, P. 1991. ‘Gastro-Intestinal Absorption of Lead in Children and Adults: Overview of Biological and Biophysico-Chemical Aspects’. Chemical Speciation and Bioavailability 3 (3–4): 87–104.Google Scholar
Mussolin, C., De Volder, A., Grandin, C., et al. 2010. ‘Neural Correlates of Symbolic Number Comparison in Developmental Dyscalculia’. Journal of Cognitive Neuroscience 22 (5): 860–74.Google Scholar
Mussolin, C., Mejias, S., and Noël, M.-P.. 2010. ‘Symbolic and Nonsymbolic Number Comparison in Children with and without Dyscalculia’. Cognition 115 (1): 10–25.Google Scholar
Myers, G. J., Davidson, P. W., Cox, C., et al. 2003. ‘Prenatal Methylmercury Exposure from Ocean Fish Consumption in the Seychelles Child Development Study’. The Lancet 361 (9370): 1686–92.Google Scholar
Myers, G. J., Davidson, P. W., and Weiss, B.. 2020. ‘Methyl Mercury Exposure and Poisoning at Niigata, Japan’. Neurotoxicology 81 (December): 358–9.Google Scholar
Myers, R. E. 1972. ‘Two Patterns of Perinatal Brain Damage and Their Conditions of Occurrence’. American Journal of Obstetrics and Gynecology 112 (2): 246–76.Google Scholar
Myers, R. E. 1975. ‘Fetal Asphyxia due to Umbilical Cord Compression. Metabolic and Brain Pathologic Consequences’. Biology of the Neonate 26 (1–2): 21–43.Google Scholar
Nag, S. 2016. Assessment Of Literacy And Foundational Learning In Developing Countries: www.heart-resources.org/wp-content/uploads/2017/06/Assessment-of-literacy-and-foundational-learning-in-developing-countries.pdf.Google Scholar
Nagy, Z., Westerberg, H., Skare, S., et al. 2003. ‘Preterm Children Have Disturbances of White Matter at 11 Years of Age as Shown by Diffusion Tensor Imaging’. Pediatric Research 54 (5): 672–9.Google Scholar
Namkung, J. M., Peng, P., and Lin, X.. 2019. ‘The Relation between Mathematics Anxiety and Mathematics Performance Among School-Aged Students: A Meta-Analysis’. Review of Educational Research 89 (3): 459–96.Google Scholar
Naranjo, V. I., Hendricks, M., and Jones, K. S.. 2020. ‘Lead Toxicity in Children: An Unremitting Public Health Problem’. Pediatric Neurology 113 (December): 51–5.Google Scholar
Nation, K. 2019. Children’s Reading Difficulties, Language, and Reflections on the Simple View of Reading, Australian Journal of Learning Difficulties, 24:1, 47–73.Google Scholar
Nation, K. (2007). Children’s reading comprehension difficulties. In M. J. Snowling, & C. Hulme (Hrsg), The science of reading (S. 248–265). Malden, MA: Blackwell.Google Scholar
National Center on Response to Intervention (NCRTI). 2010. Essential Components of RTI – A Closer Look at Response to Intervention. National Center on Response to Intervention (NCRTI) (2012). Progress Monitoring Tools.Google Scholar
Nava-Ruiz, C., Méndez-Armenta, M., and Ríos, C.. 2012. ‘Lead Neurotoxicity: Effects on Brain Nitric Oxide Synthase’. Journal of Molecular Histology 43 (5): 553–63.Google Scholar
Nelson, G., and Powell, S. R.. 2018. ‘A Systematic Review of Longitudinal Studies of Mathematics Difficulty’. Journal of Learning Disabilities 51 (6): 523–39.Google Scholar
Nguyen, L. 2019. ‘Cell Migration Promotes Dynamic Cellular Interactions to Control Cerebral Cortex Morphogenesis’. IBRO Reports 6: S8. https://doi.org/10.1016/j.ibror.2019.07.009.Google Scholar
Nicolson, R. I., and Fawcett, A. J.. 1990. ‘Automaticity: A New Framework for Dyslexia Research?’ Cognition 35 (2): 159–82.Google Scholar
Nicolson, R. I., Fawcett, A. J., and Dean, P.. 2001. ‘Developmental Dyslexia: The Cerebellar Deficit Hypothesis’. Trends in Neurosciences 24 (9): 508–11.Google Scholar
Nicolson, R. I., and Fawcett, A. J.. 2018. ‘Procedural Learning, Dyslexia and Delayed Neural Commitment’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 235–69. Springer International Publishing.Google Scholar
Nieder, A. 2016. ‘The Neuronal Code for Number’. Nature Reviews Neuroscience 17: 366–82. https://doi.org/10.1038/nrn.2016.40.Google Scholar
Nieder, A., and Dehaene, S.. 2009. ‘Representation of Number in the Brain’. Annual Review of Neuroscience 32: 185–208.Google Scholar
Nieder, A., Freedman, D. J., and Miller, E. K.. 2002. ‘Representation of the Quantity of Visual Items in the Primate Prefrontal Cortex’. Science 297 (5587): 1708–11.Google Scholar
Niederhofer, H., and Reiter, A.. 2004. ‘Prenatal Maternal Stress, Prenatal Fetal Movements and Perinatal Temperament Factors Influence Behavior and School Marks at the Age of 6 Years’. Fetal Diagnosis and Therapy 19 (2): 160–2.Google Scholar
Ni, M., Li, X., Rocha, J. B. T., Farina, M, and Aschner, M.. 2012. ‘Glia and Methylmercury Neurotoxicity’. Journal of Toxicology and Environmental Health. Part A 75 (16–17): 1091–101.Google Scholar
Niogi, S. N., and McCandliss, B. D.. 2006. ‘Left Lateralized White Matter Microstructure Accounts for Individual Differences in Reading Ability and Disability’. Neuropsychologia 44 (11): 2178–88.Google Scholar
No Child Left Behind Act of 2001 (NCLB), Public Law 107-110. 20 USC 6301.Google Scholar
Noble, K. G., Norman, M. F, and Farah, Ma. J.. 2005. ‘Neurocognitive Correlates of Socioeconomic Status in Kindergarten Children’. Developmental Science 8 (1): 74–87.Google Scholar
Norton, E. S., and Wolf, M.. 2012. ‘Rapid Automatized Naming (RAN) and Reading Fluency: Implications for Understanding and Treatment of Reading Disabilities’. Annual Review of Psychology 63: 427–52.Google Scholar
Notebaert, K., Nelis, S., and Reynvoet, B.. 2011. ‘The Magnitude Representation of Small and Large Symbolic Numbers in the Left and Right Hemisphere: An Event-Related fMRI Study’. Journal of Cognitive Neuroscience 23 (3): 622–30. https://doi.org/10.1162/jocn.2010.21445.Google Scholar
Novita, S. 2016. ‘Secondary Symptoms of Dyslexia: A Comparison of Self-Esteem and Anxiety Profiles of Children with and without Dyslexia’. European Journal of Special Needs Education 31 (2): 279–88.Google Scholar
Núñez, R. E. 2017. ‘Is There Really an Evolved Capacity for Number?’ Trends in Cognitive Sciences 21 (6): 409–24.Google Scholar
Nyaradi, A., Oddy, W. H., Hickling, S., Li, J., and Foster, J. K.. 2015. ‘The Relationship between Nutrition in Infancy and Cognitive Performance during Adolescence’. Frontiers in Nutrition 2 (February): 2.Google Scholar
O’Brien, G., and Yeatman, J. D.. 2021. ‘Bridging Sensory and Language Theories of Dyslexia: Toward a Multifactorial Model’. Developmental Science 24 (3): e13039. https://doi.org/10.1111/desc.13039.Google Scholar
Oddy, W. H., Li, J., Whitehouse, A. J. O., Zubrick, S. R., and Malacova, E.. 2011. ‘Breastfeeding Duration and Academic Achievement at 10 Years’. Pediatrics 127 (1): e137–45.Google Scholar
OECD. 2013. PISA 2012 Results: Ready to Learn (Volume III) Students’ Engagement, Drive and Self-Beliefs: Students’ Engagement, Drive and Self-Beliefs. OECD Publishing.Google Scholar
OECD. 2016. PISA 2015 Results. OECD.Google Scholar
OECD. 2018. PISA 2018 results. www.oecd.org/pisa/publications/pisa-2018-results.htm.Google Scholar
OECD. 2020, PISA 2018 results. www.oecd-ilibrary.org/education/talis-2018-results-volume-i_1d0bc92a-en.Google Scholar
OECD, and The World Bank. 2020. ‘Infant and Young Child Feeding’. Organisation for Economic Co-Operation and Development (OECD). https://doi.org/10.1787/67fe62a3-en.Google Scholar
Oei, J. L., Melhuish, E., Uebel, H., et al. 2017. ‘Neonatal Abstinence Syndrome and High School Performance’. Pediatrics 139 (2). https://doi.org/10.1542/peds.2016-2651.Google Scholar
Ogundimu, E. O., Altman, D. G., and Collins, G. S.. 2016. ‘Adequate Sample Size for Developing Prediction Models Is Not Simply Related to Events per Variable’. Journal of Clinical Epidemiology 76 (August): 175–82.Google Scholar
O’Hare, E. D., Kan, E., Yoshii, J., et al. 2005. ‘Mapping Cerebellar Vermal Morphology and Cognitive Correlates in Prenatal Alcohol Exposure’. Neuroreport 16 (12): 1285–90.Google Scholar
Oken, E., Wright, R. O., Kleinman, K. P., et al. 2005. ‘Maternal Fish Consumption, Hair Mercury, and Infant Cognition in a US Cohort’. Environmental Health Perspectives 113 (10): 1376–80.Google Scholar
Oliver, A., Johnson, M. H., Karmiloff-Smith, A., and Pennington, B.. 2000. ‘Deviations in the Emergence of Representations: A Neuroconstructivist Framework for Analysing Developmental Disorders’. Developmental Science 3 (1): 1–23.Google Scholar
Oliver, B., Harlaar, N, Thomas, M. E. H., et al. 2004. ‘A Twin Study of Teacher-Reported Mathematics Performance and Low Performance in 7-Year-Olds’. Journal of Educational Psychology 96 (3): 504–17.Google Scholar
Olson, H. C., Feldman, J. J., Streissguth, A. P., Sampson, P. D., and Bookstein, F. L.. 1998. ‘Neuropsychological Deficits in Adolescents with Fetal Alcohol Syndrome: Clinical Findings’. Alcoholism, Clinical and Experimental Research 22 (9): 1998–2012.Google Scholar
Olulade, O. A., Flowers, D. L., Napoliello, E. M., and Eden, G. F.. 2015. ‘Dyslexic Children Lack Word Selectivity Gradients in Occipito-Temporal and Inferior Frontal Cortex’. NeuroImage: Clinical 7: 742–54.Google Scholar
Olulade, O. A., Napoliello, E. M., and Eden, G. F.. 2013. ‘Abnormal Visual Motion Processing Is Not a Cause of Dyslexia’. Neuron 79 (1): 180–90.Google Scholar
O’Reilly, R. C. 1998. ‘Six Principles for Biologically Based Computational Models of Cortical Cognition’. Trends in Cognitive Sciences 2 (11): 455–62.Google Scholar
Osmon, D. C., Smerz, J. M., Braun, M. M., and Plambeck, E.. 2006. ‘Processing Abilities Associated with Math Skills in Adult Learning Disability’. Journal of Clinical and Experimental Neuropsychology 28 (1): 84–95.Google Scholar
Ostad, S. A. 1997. ‘Developmental Differences in Addition Strategies: A Comparison of Mathematically Disabled and Mathematically Normal Children’. British Journal of Educational Psychology 67 (Pt 3) (September): 345–57.Google Scholar
Ostad, S. A. 1998. ‘Developmental Differences in Solving Simple Arithmetic Word Problems and Simple Number-Fact Problems: A Comparison of Mathematically Normal and Mathematically Disabled Children’. Mathematical Cognition 4 (1): 1–19. https://doi.org/10.1080/135467998387389.Google Scholar
Ou, X., Andres, A., Pivik, R. T., et al. 2016. ‘Voxel-Based Morphometry and fMRI Revealed Differences in Brain Gray Matter in Breastfed and Milk Formula-Fed Children’. AJNR. American Journal of Neuroradiology 37 (4): 713–19.Google Scholar
Ozernov-Palchik, O., and Gaab, N.. 2016. ‘Tackling the ‘Dyslexia Paradox’: Reading Brain and Behavior for Early Markers of Developmental Dyslexia’. Wiley Interdisciplinary Reviews. Cognitive Science 7 (2): 156–76.Google Scholar
Pagliarini, E., Guasti, M. T., Toneatto, C., et al. 2015. ‘Dyslexic Children Fail to Comply with the Rhythmic Constraints of Handwriting’. Human Movement Science 42 (August): 161–82.Google Scholar
Pantoja, N., Schaeffer, M. W., Rozek, C. S., Beilock, S. L., and Levine, S. C.. 2020. ‘Children’s Math Anxiety Predicts Their Math Achievement Over and Above a Key Foundational Math Skill’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 21 (5): 709–28.Google Scholar
Papanikolaou, N. C., Hatzidaki, E. G., Belivanis, S., Tzanakakis, G. N., and Tsatsakis, A. M.. 2005. ‘Lead Toxicity Update. A Brief Review’. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research 11 (10): RA329–36.Google Scholar
Park, D., Ramirez, G., and Beilock, S. L.. 2014. ‘The Role of Expressive Writing in Math Anxiety’. Journal of Experimental Psychology. Applied 20 (2): 103–11.Google Scholar
Park, J. 2018. ‘A Neural Basis for the Visual Sense of Number and Its Development: A Steady-State Visual Evoked Potential Study in Children and Adults’. Developmental Cognitive Neuroscience 30 (April): 333–43.Google Scholar
Park, J., Li, R., and Brannon, E. M.. 2014. ‘Neural Connectivity Patterns Underlying Symbolic Number Processing Indicate Mathematical Achievement in Children’. Developmental Science 17 (2): 187–202.Google Scholar
Pasquini, E. S., Corriveau, K. H., and Goswami, U.. 2007. ‘Auditory Processing of Amplitude Envelope Rise Time in Adults Diagnosed With Developmental Dyslexia’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 11 (3): 259–86.Google Scholar
Passolunghi, M. C., De Vita, C., and Pellizzoni, S.. 2020. ‘Math Anxiety and Math Achievement: The Effects of Emotional and Math Strategy Training’. Developmental Science 23 (6): e12964.Google Scholar
Patandin, S., Lanting, C. I., Mulder, P. G. H., et al. 1999. ‘Effects of Environmental Exposure to Polychlorinated Biphenyls and Dioxins on Cognitive Abilities in Dutch Children at 42 Months of Age’. The Journal of Pediatrics 134 (1): 33–41.Google Scholar
Paterson, S. J., Parish-Morris, J., Hirsh-Pasek, K., and Michnick Golinkoff, R. 2016. ‘Considering Development in Developmental Disorders’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 17 (4): 568–83.Google Scholar
Patra, K., Wilson-Costello, D., Taylor, H. G., Mercuri-Minich, N., and Hack, M.. 2006. ‘Grades I-II Intraventricular Hemorrhage in Extremely Low Birth Weight Infants: Effects on Neurodevelopment’. The Journal of Pediatrics 149 (2): 169–73.Google Scholar
Paulesu, E., Démonet, J. F., Fazio, F., et al. 2001. ‘Dyslexia: Cultural Diversity and Biological Unity’. Science 291 (5511): 2165–7.Google Scholar
Paulesu, E., Bonandrini, R., Zapparoli, L., et al. 2021. ‘Effects of Orthographic Consistency on Bilingual Reading: Human and Computer Simulation Data’. Brain Sciences 11 (7). https://doi.org/10.3390/brainsci11070878.Google Scholar
Paulson, J. A., and Brown, M. J.. 2019. ‘The CDC Blood Lead Reference Value for Children: Time for a Change’. Environmental Health 18 (16). https://doi.org/10.1186/s12940-019-0457-7.Google Scholar
Paus, T. 2005. ‘Mapping Brain Maturation and Cognitive Development during Adolescence’. Trends in Cognitive Sciences 9 (2): 60–8.Google Scholar
Peacock, A., Leung, J., Larney, S., et al. 2018. ‘Global Statistics on Alcohol, Tobacco and Illicit Drug Use: 2017 Status Report’. Addiction 113 (10): 1905–26.Google Scholar
Pearson, R. M., Bornstein, M. H., Cordero, M., et al. 2016. ‘Maternal Perinatal Mental Health and Offspring Academic Achievement at Age 16: The Mediating Role of Childhood Executive Function’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 57 (4): 491–501.Google Scholar
Pegg, J. and Graham, L.. 2013. ‘A Three-Level Intervention Pedagogy to Enhance the Academic Achievement of Indigenous Students: Evidence From QuickSmart’. In R. Jorgenson, P. Sullivan and P. Grootenboer (eds.), Pedagogies to Enhance Learning for Indigenous Students, 123–38). Springer.Google Scholar
Pekrun, R., Elliot, A. J., and Maier, M. A.. 2006. ‘Achievement Goals and Discrete Achievement Emotions: A Theoretical Model and Prospective Test’. Journal of Educational Psychology 98 (3): 583–97.Google Scholar
Peng, P., and Fuchs, D.. 2016. ‘A Meta-Analysis of Working Memory Deficits in Children With Learning Difficulties: Is There a Difference between Verbal Domain and Numerical Domain?’ Journal of Learning Disabilities 49 (1): 3–20.Google Scholar
Pennington, B. 2006. ‘From Single to Multiple Deficit Models of Developmental Disorders’. Cognition. https://doi.org/10.1016/j.cognition.2006.04.008.Google Scholar
Pennington, B. F., McGrath, L. M., and Peterson, R. L.. 2019. Diagnosing Learning Disorders, Third Edition: From Science to Practice. Guilford Publications.Google Scholar
Perry, C., Ziegler, J. C., Braun, M., and Zorzi, M.. 2010. ‘Rules versus Statistics in Reading Aloud: New Evidence on an Old Debate’. The European Journal of Cognitive Psychology 22 (5): 798–812.Google Scholar
Perry, C., Ziegler, J. C., and Zorzi, M.. 2007. ‘Nested Incremental Modeling in the Development of Computational Theories: The CDP+ Model of Reading Aloud’. Psychological Review 114 (2): 273–315.Google Scholar
Perry, C., Ziegler, J. C., and Zorzi, M. 2010. ‘Beyond Single Syllables: Large-Scale Modeling of Reading Aloud with the Connectionist Dual Process (CDP++) Model’. Cognitive Psychology 61 (2): 106–51.Google Scholar
Perry, C., Ziegler, J. C., and Zorzi, M. 2014a. ‘When Silent Letters Say More than a Thousand Words: An Implementation and Evaluation of CDP++ in French’. Journal of Memory and Language 72 (April): 98–115.Google Scholar
Perry, C., Ziegler, J. C., and Zorzi, M. 2014b. ‘CDP++.Italian: Modelling Sublexical and Supralexical Inconsistency in a Shallow Orthography’. PloS One 9 (4): e94291.Google Scholar
Perry, C., Zorzi, M., and Ziegler, J. C.. 2019. ‘Understanding Dyslexia Through Personalized Large-Scale Computational Models’. Psychological Science 30 (3): 386–95.Google Scholar
Peters, L., and Ansari, D.. 2019. ‘Are Specific Learning Disorders Truly Specific, and Are They Disorders?’ Trends in Neuroscience and Education 17 (December): 100115.Google Scholar
Peters, L., Bulthé, J., Daniels, N., Op de, H Beeck, and B. De Smedt, . 2018. ‘Dyscalculia and Dyslexia: Different Behavioral, yet Similar Brain Activity Profiles during Arithmetic’. NeuroImage: Clinical 18: 663–74. https://doi.org/10.1016/j.nicl.2018.03.003.Google Scholar
Peters, L., and De Smedt, B.. 2018. ‘Arithmetic in the Developing Brain: A Review of Brain Imaging Studies’. Developmental Cognitive Neuroscience 30: 265–79. https://doi.org/10.1016/j.dcn.2017.05.002.Google Scholar
Peters, L., Op de Beeck, H, and De Smedt, B.. 2020. ‘Cognitive Correlates of Dyslexia, Dyscalculia and Comorbid Dyslexia/dyscalculia: Effects of Numerical Magnitude Processing and Phonological Processing’. Research in Developmental Disabilities 107: 103806. https://doi.org/10.1016/j.ridd.2020.103806.Google Scholar
Peters, L. L., Thornton, C., de Jonge, A., et al. 2018. ‘The Effect of Medical and Operative Birth Interventions on Child Health Outcomes in the First 28 Days and up to 5 Years of Age: A Linked Data Population-Based Cohort Study’. Birth 45 (4): 347–57.Google Scholar
Peterson, R. L., Boada, R., McGrath, L. M., et al. 2017. ‘Cognitive Prediction of Reading, Math, and Attention: Shared and Unique Influences’. Journal of Learning Disabilities 50 (4): 408–21.Google Scholar
Peterson, R.L., and Pennington, B. F.. 2012. ‘Developmental Dyslexia’. The Lancet 379 (9830): 1997–2007.Google Scholar
Peterson, R.L., and Pennington, B. F. 2015. ‘Developmental Dyslexia’. Annual Review of Clinical Psychology 11 (January): 283–307.Google Scholar
Peterson, R. L., Pennington, B. F., and Olson, R. K.. 2013. ‘Subtypes of Developmental Dyslexia: Testing the Predictions of the Dual-Route and Connectionist Frameworks’. Cognition 126 (1): 20–38.Google Scholar
Petryk, A., Harris, S. R., and Jongbloed, L.. 2007. ‘Breastfeeding and Neurodevelopment’. Infants and Young Children 20 (2): 120–34.Google Scholar
Pezzulo, G., Zorzi, M., and Corbetta, M.. 2021. ‘The Secret Life of Predictive Brains: What’s Spontaneous Activity For?’ Trends in Cognitive Sciences, 25 (9): P730–43. https://doi.org/10.1016/j.tics.2021.05.007.Google Scholar
Piazza, M., Facoetti, A., Trussardi, A. N., et al. 2010. ‘Developmental Trajectory of Number Acuity Reveals a Severe Impairment in Developmental Dyscalculia’. Cognition 116 (1): 33–41.Google Scholar
Piazza, M., Giacomini, E., Le Bihan, D., and Dehaene, S.. 2003. ‘Single-Trial Classification of Parallel Pre-Attentive and Serial Attentive Processes Using Functional Magnetic Resonance Imaging’. Proceedings. Biological Sciences / The Royal Society 270 (1521): 1237–45.Google Scholar
Piazza, M., Izard, V., Pinel, P., Le Bihan, D., and Dehaene, S.. 2004. ‘Tuning Curves for Approximate Numerosity in the Human Intraparietal Sulcus’. Neuron 7: e1109. https://doi.org/10.1016/j.neuron.2004.10.014.Google Scholar
Piazza, M., Pinel, P., Le Bihan, D., and Dehaene, S.. 2007. ‘A Magnitude Code Common to Numerosities and Number Symbols in Human Intraparietal Cortex’. Neuron 53 (2): 293–305.Google Scholar
Piccolo, L. R., Giacomoni, C. H., Julio-Costa, A., et al. 2017. ‘Reading Anxiety in L1: Reviewing the Concept’. Early Childhood Education Journal 45 (4): 537–43.Google Scholar
Pieper, I., Wehe, C. A., Bornhorst, J., et al. 2014. ‘Mechanisms of Hg Species Induced Toxicity in Cultured Human Astrocytes: Genotoxicity and DNA-Damage Response’. Metallomics: Integrated Biometal Science 6 (3): 662–71.Google Scholar
Pietron, W., Pajurek, M., Mikolajczyk, S., et al. 2019. ‘Exposure to PBDEs Associated with Farm Animal Meat Consumption’. Chemosphere 224 (June): 58–64.Google Scholar
Pievsky, M. A., and McGrath, R. E.. 2018. ‘The Neurocognitive Profile of Attention-Deficit/Hyperactivity Disorder: A Review of Meta-Analyses’. Archives of Clinical Neuropsychology: The Official Journal of the National Academy of Neuropsychologists 33 (2): 143–57.Google Scholar
Pitsia, V., Biggart, A., and Karakolidis, A.. 2017. ‘The Role of Students’ Self-Beliefs, Motivation and Attitudes in Predicting Mathematics Achievement: A Multilevel Analysis of the Programme for International Student Assessment Data’. Learning and Individual Differences 55 (April): 163–73.Google Scholar
Pixner, S., Moeller, K., Hermanova, V., Nuerk, H.-C., & Kaufmann, L. (2011a). Whorf reloaded: Language effects on nonverbal number processing in first grade – A trilingual study. Journal of Experimental Child Psychology, 108, 371–382. http://dx.doi.org/10.1016/j.jecp.2010.09.002.Google Scholar
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., and Patterson, K.. 1996. ‘Understanding Normal and Impaired Word Reading: Computational Principles in Quasi-Regular Domains’. Psychological Review 103 (1): 56–115.Google Scholar
Pleisch, G., Karipidis, I. I., Brauchli, C., et al. 2019. ‘Emerging Neural Specialization of the Ventral Occipitotemporal Cortex to Characters through Phonological Association Learning in Preschool Children’. NeuroImage 189 (April): 813–31.Google Scholar
Plomin, R., DeFries, J. C., and Loehlin, J. C.. 1977. ‘Genotype-Environment Interaction and Correlation in the Analysis of Human Behavior’. Psychological Bulletin 84 (2): 309–22.Google Scholar
Plomin, R. 2014. ‘Genotype-Environment Correlation in the Era of DNA’. Behavior Genetics 44 (6): 629–38.Google Scholar
Plomin, R, and Kovas, Y. 2005. ‘Generalist Genes and Learning Disabilities’. Psychological Bulletin 131 (4): 592–617.Google Scholar
Pocock, S. J., Smith, M., and Baghurst, P.. 1994. ‘Environmental Lead and Children’s Intelligence: A Systematic Review of the Epidemiological Evidence’. BMJ 309 (6963): 1189–97.Google Scholar
Poelmans, H., Luts, H., Vandermosten, M., et al. 2011. ‘Reduced Sensitivity to Slow-Rate Dynamic Auditory Information in Children with Dyslexia’. Research in Developmental Disabilities 32 (6): 2810–19.Google Scholar
Poldrack, R. A. 2000. ‘Imaging Brain Plasticity: Conceptual and Methodological Issues–a Theoretical Review’. NeuroImage 12 (1): 1–13.Google Scholar
Polidano, C., Zhu, A., and Bornstein, J. C.. 2017. ‘The Relation between Cesarean Birth and Child Cognitive Development’. Scientific Reports 7 (1): 11483.Google Scholar
Pong, K. M., Abdel-Latif, M. E., Lui, K, et al. 2010. ‘The Temporal Influence of a Heroin Shortage on Pregnant Drug Users and Their Newborn Infants in Sydney, Australia’. The Australian & New Zealand Journal of Obstetrics & Gynaecology 50 (3): 230–6.Google Scholar
Powell, S. R., Fuchs, L. S., Fuchs, D., Cirino, P. T., and Fletcher, J. M.. 2009a. ‘Effects of Fact Retrieval Tutoring on Third-Grade Students with Math Difficulties with and without Reading Difficulties’. Learning Disabilities Research & Practice: A Publication of the Division for Learning Disabilities, Council for Exceptional Children 24 (1): 1–11.Google Scholar
Powell, S. R., Fuchs, L. S., Fuchs, D., Cirino, P. T., and Fletcher, J. M. 2009b. ‘Do Word-Problem Features Differentially Affect Problem Difficulty as a Function of Students’ Mathematics Difficulty with and without Reading Difficulty?’ Journal of Learning Disabilities 42 (2): 99–110.Google Scholar
Power, A. J., Colling, L. J., Mead, N., Barnes, L., and Goswami, U.. 2016. ‘Neural Encoding of the Speech Envelope by Children with Developmental Dyslexia’. Brain and Language 160 (September): 1–10.Google Scholar
Power, A. J., Mead, N., Barnes, L., and Goswami, U.. 2013. ‘Neural Entrainment to Rhythmic Speech in Children with Developmental Dyslexia’. Frontiers in Human Neuroscience 7 (November): 777.Google Scholar
Power, J. D., Cohen, A. L., Nelson, S. M., et al. 2011. ‘Functional Network Organization of the Human Brain’. Neuron 72 (4): 665–78.Google Scholar
Prado, J., Mutreja, R., and Booth, J. R.. 2014. ‘Developmental Dissociation in the Neural Responses to Simple Multiplication and Subtraction Problems’. Developmental Science 17 (4): 537–52.Google Scholar
Pressman, J. and Wildavsky, A.. 1973. Implementation. University of California Press.Google Scholar
Preston, J. L., Molfese, P. J., Frost, S. J., et al. 2016. ‘Print-Speech Convergence Predicts Future Reading Outcomes in Early Readers’. Psychological Science 27 (1): 75–84.Google Scholar
Price, C. J., and Devlin, J. T.. 2011. ‘The Interactive Account of Ventral Occipitotemporal Contributions to Reading’. Trends in Cognitive Sciences 15 (6): 246–53.Google Scholar
Price, C. J. 2000. ‘The Anatomy of Language: Contributions from Functional Neuroimaging’. Journal of Anatomy 197 Pt 3 (October): 335–59.Google Scholar
Price, G. R., Holloway, I., Räsänen, P., Vesterinen, M., and Ansari, D.. 2007. ‘Impaired Parietal Magnitude Processing in Developmental Dyscalculia’. Current Biology 17 (24): PR1042–R1043. https://doi.org/10.1016/j.cub.2007.10.013.Google Scholar
Price, G. R., Yeo, D. J., Wilkey, E. D., and Cutting, L. E.. 2018. ‘Prospective Relations between Resting-State Connectivity of Parietal Subdivisions and Arithmetic Competence’. Developmental Cognitive Neuroscience 30 (April): 280–90.Google Scholar
Primi, C., Busdraghi, C., Tomasetto, C., Morsanyi, K., and Chiesi, F.. 2014. ‘Measuring Math Anxiety in Italian College and High School Students: Validity, Reliability and Gender Invariance of the Abbreviated Math Anxiety Scale (AMAS)’. Learning and Individual Differences 34 (August): 51–56.Google Scholar
Pritchard, V. E., Malone, S. A., & Hulme, C. (2021). Early handwriting ability predicts the growth of children’s spelling, but not reading, skills. Scientific Studies of Reading, 25(4), 304–318. https://doi.org/10.1080/10888438.2020.1778705.Google Scholar
Pugh, K. R., Frost, S. J., Rothman, D. L., et al. 2014. ‘Glutamate and Choline Levels Predict Individual Differences in Reading Ability in Emergent Readers’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 34 (11): 4082–9.Google Scholar
Pugh, K. R., Frost, S. J., Sandak, R., et al. 2012. ‘Mapping the Word Reading Circuitry in Skilled and Disabled Readers’. In The Neural Basis of Reading, 281–305. Psychology Press.Google Scholar
Pulli, E. P., Kumpulainen, V, Kasurinen, J. H., et al. 2019. ‘Prenatal Exposures and Infant Brain: Review of Magnetic Resonance Imaging Studies and a Population Description Analysis’. Human Brain Mapping 40 (6): 1987–2000.Google Scholar
Punaro, L., and Reeve, R.. 2012. ‘Relationships between 9-Year-Olds’ Math and Literacy Worries and Academic Abilities’. Child Development Research 2012 (October). https://doi.org/10.1155/2012/359089.Google Scholar
Purpura, D. J., and Ganley, C. M.. 2014. ‘Working Memory and Language: Skill-Specific or Domain-General Relations to Mathematics?’ Journal of Experimental Child Psychology 122 (June): 104–21.Google Scholar
Qin, S., Cho, S., Chen, T., et al. 2014. ‘Hippocampal-Neocortical Functional Reorganization Underlies Children’s Cognitive Development’. Nature Neuroscience 17: 1263–9. https://doi.org/10.1038/nn.3788.Google Scholar
Quantities, Counting, Numbers (MZZ). n.d. Understanding the World of Mathematics. Support Boxes for Day-Care Centres and Initial Lessons: www.cornelsen.de/produkte/foerderboxen-fuer-kita-und-anfangsunterricht-mengen-zaehlen-zahlen-mzz-die-welt-der-mathematik-verstehen-koffer-mit-foerdermaterialien-und-handreichungen-80-s-9783060800155.Google Scholar
Raddatz, J., Kuhn, J.-T., Holling, H., Moll, K., and Dobel, C.. 2017. ‘Comorbidity of Arithmetic and Reading Disorder: Basic Number Processing and Calculation in Children With Learning Impairments’. Journal of Learning Disabilities 50 (3): 298–308.Google Scholar
Rafferty, J., Mattson, G, Earls, M. F., Yogman, M. W., and Committee on Psychosocial Aspects of Child and Family Health. 2019. ‘Incorporating Recognition and Management of Perinatal Depression Into Pediatric Practice’. Pediatrics 143 (1): e20183260. https://doi.org/10.1542/peds.2018-3260.Google Scholar
Ragnarsdottir, L. D., Kristjansson, A. L., Thorisdottir, I. E., et al. 2017. ‘Cumulative Risk over the Early Life Course and Its Relation to Academic Achievement in Childhood and Early Adolescence’. Preventive Medicine 96 (March): 36–41.Google Scholar
Ramaa, S., and Gowramma, I. P.. 2002. A Systematic Procedure for Identifying and Classifying Children with Dyscalculia Among Primary School. Dyslexia 8: 67–85.Google Scholar
Raman, D. V., Rotondo, A. P., and O’Leary, T.. 2019. ‘Fundamental Bounds on Learning Performance in Neural Circuits’. Proceedings of the National Academy of Sciences of the United States of America 116 (21): 10537–46.Google Scholar
Ramirez, G., and Beilock, S. L.. 2011. ‘Writing about Testing Worries Boosts Exam Performance in the Classroom’. Science 331 (6014): 211–13.Google Scholar
Ramirez, G., Chang, H, Maloney, E. A., Levine, S. C., and Beilock, S. L.. 2016. ‘On the Relationship between Math Anxiety and Math Achievement in Early Elementary School: The Role of Problem Solving Strategies’. Journal of Experimental Child Psychology 141 (January): 83–100.Google Scholar
Ramirez, G., Shaw, S. T., and Maloney, E. A.. 2018. ‘Math Anxiety: Past Research, Promising Interventions, and a New Interpretation Framework’. Educational Psychologist 53 (3): 145–64.Google Scholar
Ranasinghe, S., Or, G., Wang, E. Y., et al. 2015. ‘Reduced Cortical Activity Impairs Development and Plasticity after Neonatal Hypoxia Ischemia’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 35 (34): 11946–59.Google Scholar
Ranpura, A., Isaacs, E., Edmonds, C., et al. 2013. ‘Developmental Trajectories of Grey and White Matter in Dyscalculia’. Trends in Neuroscience and Education 2 (2): 56–64.Google Scholar
Rantalainen, V., Lahti, J., Henriksson, M., et al. 2018. ‘Association between Breastfeeding and Better Preserved Cognitive Ability in an Elderly Cohort of Finnish Men’. Psychological Medicine 48 (6): 939–51.Google Scholar
Raschle, N. M., Stering, P. L., Meissner, S. N., and Gaab, N.. 2014. ‘Altered Neuronal Response during Rapid Auditory Processing and Its Relation to Phonological Processing in Prereading Children at Familial Risk for Dyslexia’. Cerebral Cortex 24 (9): 2489–501.Google Scholar
Rasmussen, C., and Bisanz, J.. 2011. ‘The Relation between Mathematics and Working Memory in Young Children With Fetal Alcohol Spectrum Disorders’. The Journal of Special Education 45 (3): 184–91.Google Scholar
Rätsep, M. T., Paolozza, A., Hickman, A. F., et al. 2016. ‘Brain Structural and Vascular Anatomy Is Altered in Offspring of Pre-Eclamptic Pregnancies: A Pilot Study’. AJNR. American Journal of Neuroradiology 37 (5): 939–45.Google Scholar
Read, Charles. 1986. Children’s Creative Spelling. Routledge.Google Scholar
Remer, J., Croteau-Chonka, E., Dean, D. C. 3rd, et al. 2017. ‘Quantifying Cortical Development in Typically Developing Toddlers and Young Children, 1–6 Years of Age’. NeuroImage 153 (June): 246–61.Google Scholar
Reynolds, C. A., Hewitt, J. K., Erickson, M. T., et al. 1996. ‘The Genetics of Children’s Oral Reading Performance’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 37 (4): 425–34.Google Scholar
Reynolds, J. E., Long, X, Grohs, M. N., Dewey, D., and Lebel, C.. 2019. ‘Structural and Functional Asymmetry of the Language Network Emerge in Early Childhood’. Developmental Cognitive Neuroscience 39 (October): 100682.Google Scholar
Rice, D. C., Schoeny, R., and Mahaffey, K.. 2003. ‘Methods and Rationale for Derivation of a Reference Dose for Methylmercury by the US EPA’. Risk Analysis: An Official Publication of the Society for Risk Analysis 23 (1): 107–15.Google Scholar
Richards, M., Hardy, R., and Wadsworth, M. E. J.. 2002. ‘Long-Term Effects of Breast-Feeding in a National Birth Cohort: Educational Attainment and Midlife Cognitive Function’. Public Health Nutrition 5 (5): 631–5.Google Scholar
Richardson, F. C., and Suinn, R. M.. 1972. ‘The Mathematics Anxiety Rating Scale: Psychometric Data’. Journal of Counseling Psychology 19 (6): 551–4.Google Scholar
Richlan, F. 2020. ‘The Functional Neuroanatomy of Developmental Dyslexia Across Languages and Writing Systems’. Frontiers in Psychology 11 (February): 155.Google Scholar
Richlan, F., Kronbichler, M., and Wimmer, H.. 2009. ‘Functional Abnormalities in the Dyslexic Brain: A Quantitative Meta-Analysis of Neuroimaging Studies’. Human Brain Mapping 30 (10): 3299–308.Google Scholar
Richlan, F., Kronbichler, M., and Wimmer, H. 2011. ‘Meta-Analyzing Brain Dysfunctions in Dyslexic Children and Adults’. NeuroImage 56 (3): 1735–42.Google Scholar
Richlan, F., Kronbichler, M., and Wimmer, H. 2013. ‘Structural Abnormalities in the Dyslexic Brain: A Meta-Analysis of Voxel-Based Morphometry Studies’. Human Brain Mapping 34 (11): 3055–65.Google Scholar
Rickard, T. C. 1997. ‘Bending the Power Law: A CMPL Theory of Strategy Shifts and the Automatization of Cognitive Skills’. Journal of Experimental Psychology. General 126 (3): 288–311.Google Scholar
Riesenhuber, M., and Glezer, L. S.. 2017. ‘Evidence for Rapid Localist Plasticity in the Ventral Visual Stream: The Example of Words’. Language, Cognition and Neuroscience 32 (3): 286–94.Google Scholar
Riesenhuber, M., and Poggio, T.. 1999. ‘Hierarchical Models of Object Recognition in Cortex’. Nature Neuroscience 2 (11): 1019–25.Google Scholar
Rimfeld, K., Malanchini, M., Spargo, T., et al. 2019. ‘Twins Early Development Study: A Genetically Sensitive Investigation into Behavioral and Cognitive Development from Infancy to Emerging Adulthood’. Twin Research and Human Genetics: The Official Journal of the International Society for Twin Studies 22 (6): 508–13.Google Scholar
Ríos-López, P., Molinaro, N., and Lallier, M.. 2019. ‘Tapping to a Beat in Synchrony Predicts Brain Print Sensitivity in Pre-Readers’. Brain and Language 199 (December): 104693.Google Scholar
Rivera, S. M., Reiss, A. L., Eckert, M. A., and Menon, V.. 2005. ‘Developmental Changes in Mental Arithmetic: Evidence for Increased Functional Specialization in the Left Inferior Parietal Cortex’. Cerebral Cortex 15 (11): 1779–90.Google Scholar
Robertson, C. M. T. 2003. ‘Long-Term Follow-up of Term Infants with Perinatal Asphyxia’. In D. Stevenson, W. Benitz and P. Sunshine (eds.), Fetal and Neonatal Brain Injury: Mechanisms, Management and the Risks of Practice, 829–58. Cambridge University Press.Google Scholar
Robinson, C. S., Menchetti, B. M., and Torgesen, J. K.. 2002. ‘Toward a Two-Factor Theory of One Type of Mathematics Disabilities’. Learning Disabilities Research and Practice 17 (2): 81–9. https://doi.org/10.1111/1540-5826.00035.Google Scholar
Rochelle, K. S. H., and Talcott, J. B. 2006. ‘Impaired Balance in Developmental Dyslexia? A Meta-Analysis of the Contending Evidence’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 47 (11): 1159–66.Google Scholar
Rodríguez-Martínez, E. I., Ruiz-Martínez, F. J., Barriga Paulino, C. I., and Gómez, C. M.. 2017. ‘Frequency Shift in Topography of Spontaneous Brain Rhythms from Childhood to Adulthood’. Cognitive Neurodynamics 11 (1): 23–33.Google Scholar
Roeske, D., Ludwig, K. U., Neuhoff, N., et al. 2011. ‘First Genome-Wide Association Scan on Neurophysiological Endophenotypes Points to Trans-Regulation Effects on SLC2A3 in Dyslexic Children’. Molecular Psychiatry 16: 97–107. https://doi.org/10.1038/mp.2009.102.Google Scholar
Rogers, A., Obst, S., Teague, S. J., et al. 2020. ‘Association between Maternal Perinatal Depression and Anxiety and Child and Adolescent Development: A Meta-Analysis’. JAMA Pediatrics 174 (11): 1082–92.Google Scholar
Romeo, R. R., Christodoulou, J. A., Halverson, K. K., et al. 2017. ‘Socioeconomic Status and Reading Disability: Neuroanatomy and Plasticity in Response to Intervention’. Cerebral Cortex 91 (2): 1–16.Google Scholar
Roncero, C., Valriberas-Herrero, I., Mezzatesta-Gava, M, et al. 2020. ‘Cannabis Use during Pregnancy and Its Relationship with Fetal Developmental Outcomes and Psychiatric Disorders. A Systematic Review’. Reproductive Health 17 (1): 25.Google Scholar
Roos, D. H., Puntel, R. L., Lugokenski, T. H., et al. 2010. ‘Complex Methylmercury-Cysteine Alters Mercury Accumulation in Different Tissues of Mice’. Basic & Clinical Pharmacology & Toxicology 107 (4): 789–92.Google Scholar
Rosenberg-Lee, M., Ashkenazi, S., Chen, T, et al. 2015. ‘Brain Hyper-Connectivity and Operation-Specific Deficits during Arithmetic Problem Solving in Children with Developmental Dyscalculia’. Developmental Science 18 (3): 351–72. https://doi.org/10.1111/desc.12216.Google Scholar
Rosenberg-Lee, M., Barth, M., and Menon, V.. 2011. ‘What Difference Does a Year of Schooling Make? Maturation of Brain Response and Connectivity between 2nd and 3rd Grades during Arithmetic Problem Solving’. NeuroImage 57 (3): 796–808.Google Scholar
Rosenberg-Lee, M., Iuculano, T., Bae, S. R., et al. 2018. ‘Short-Term Cognitive Training Recapitulates Hippocampal Functional Changes Associated with One Year of Longitudinal Skill Development’. Trends in Neuroscience and Education 10 (March): 19–29.Google Scholar
Rosen, M. G., Debanne, S. M., Thompson, K., and Dickinson, J. C.. 1992. ‘Abnormal Labor and Infant Brain Damage’. Obstetrics and Gynecology 80 (6): 961–5.Google Scholar
Ross, E. J., Graham, D. L., Money, K. M., and Stanwood, G. D.. 2015. ‘Developmental Consequences of Fetal Exposure to Drugs: What We Know and What We Still Must Learn’. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology 40 (1): 61–87.Google Scholar
Rotzer, S., Kucian, K., Martin, E., et al. 2008. ‘Optimized Voxel-Based Morphometry in Children with Developmental Dyscalculia’. NeuroImage 39 (1): 417–22.Google Scholar
Rotzer, S., Loenneker, T., Kucian, K., et al. 2009. ‘Dysfunctional Neural Network of Spatial Working Memory Contributes to Developmental Dyscalculia’. Neuropsychologia 47 (13): 2859–65.Google Scholar
Rourke, B. P., and Finlayson, M. A.. 1978. ‘Neuropsychological Significance of Variations in Patterns of Academic Performance: Verbal and Visual-Spatial Abilities’. Journal of Abnormal Child Psychology 6 (1): 121–33.Google Scholar
Rourke, B. P., and Strang, J.. 1978. Neuropsychological Significance of Variations in Patterns of Academic Performance: Motor, Psychomotor, and Tactile-Perceptual Abilities. Journal of Pediatric Psychology 3: 62–6.Google Scholar
Rousselle, L., and Noël, M.-P.. 2007. ‘Basic Numerical Skills in Children with Mathematics Learning Disabilities: A Comparison of Symbolic vs Non-Symbolic Number Magnitude Processing’. Cognition 102 (3): 361–95.Google Scholar
Roussotte, F. F., Sulik, K. K., Mattson, S. N., et al. 2012. ‘Regional Brain Volume Reductions Relate to Facial Dysmorphology and Neurocognitive Function in Fetal Alcohol Spectrum Disorders’. Human Brain Mapping 33 (4): 920–37.Google Scholar
Roux, F., and Uhlhaas, P. J.. 2014. ‘Working Memory and Neural Oscillations: α-γ versus θ-γ Codes for Distinct WM Information?’ Trends in Cognitive Sciences 18 (1): 16–25.Google Scholar
Røysamb, E., and Tambs, K.. 2016. ‘The Beauty, Logic and Limitations of Twin Studies’. Norsk Epidemiologi 26 (1–2). https://doi.org/10.5324/nje.v26i1-2.2014.Google Scholar
Roze, E., Meijer, L., Bakker, A, et al. 2009. ‘Prenatal Exposure to Organohalogens, Including Brominated Flame Retardants, Influences Motor, Cognitive, and Behavioral Performance at School Age’. Environmental Health Perspectives 117 (12): 1953–8.Google Scholar
Rozisky, J. R., Laste, G., de Macedo, I. C., et al. 2013. ‘Neonatal Morphine Administration Leads to Changes in Hippocampal BDNF Levels and Antioxidant Enzyme Activity in the Adult Life of Rats’. Neurochemical Research 38 (3): 494–503.Google Scholar
Rubenstein, J. L. R., and Merzenich, M. M.. 2003. ‘Model of Autism: Increased Ratio of Excitation/inhibition in Key Neural Systems’. Genes, Brain, and Behavior 2 (5): 255–67.Google Scholar
Rubinsten, O., and Henik, A.. 2005. ‘Automatic Activation of Internal Magnitudes: A Study of Developmental Dyscalculia’. Neuropsychology 19 (5): 641–8.Google Scholar
Rubinsten, O., and Henik, A. 2006. ‘Double Dissociation of Functions in Developmental Dyslexia and Dyscalculia’. Journal of Educational Psychology 98 (4): 854–67. https://doi.org/10.1037/0022-0663.98.4.854.Google Scholar
Rubinsten, O., and Henik, A. 2009. ‘Developmental Dyscalculia: Heterogeneity Might Not Mean Different Mechanisms’. Trends in Cognitive Sciences 13 (2): P92–9. https://doi.org/10.1016/j.tics.2008.11.002.Google Scholar
Rucinski, M., Cangelosi, A., and Belpaeme, T.. 2012. ‘Robotic Model of the Contribution of Gesture to Learning to Count’. 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL). https://doi.org/10.1109/devlrn.2012.6400579.Google Scholar
Rückinger, S., Rzehak, P., Chen, C.-M., et al. 2010. ‘Prenatal and Postnatal Tobacco Exposure and Behavioral Problems in 10-Year-Old Children: Results from the GINI-plus Prospective Birth Cohort Study’. Environmental Health Perspectives 118 (1): 150–4.Google Scholar
Rule, M. E., Loback, A. R., Raman, D. V., et al. ‘Stable Task Information from an Unstable Neural Population’. eLife 9 (July). https://doi.org/10.7554/eLife.51121.Google Scholar
Rumelhart, D. E., and McClelland, J. L. (1986). Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1: Foundations (Vol. 1; D. E. Rumelhart & J. L. McClelland, eds.). Cambridge, MA: MIT Press.Google Scholar
Rumelhart, D. E., Hinton, G. E., and Williams, R. J.. 1986. ‘Learning Representations by Back-Propagating Errors’. Nature 323 (6088): 533–6.Google Scholar
Rüsseler, J., Probst, S., Johannes, S., and Münte, T.. 2003. ‘Recognition Memory for High- and Low-Frequency Words in Adult Normal and Dyslexic Readers: An Event-Related Brain Potential Study’. Journal of Clinical and Experimental Neuropsychology 25 (6): 815–29.Google Scholar
Rykhlevskaia, E., Uddin, L. Q., Kondos, L., and Menon, V.. 2009. ‘Neuroanatomical Correlates of Developmental Dyscalculia: Combined Evidence from Morphometry and Tractography’. Frontiers in Human Neuroscience 3 (November): 51.Google Scholar
Sabatier, P. A. and Mazmanian, D.. 1983. ‘Policy Implementation’. In Dekker, M. (ed.), Encyclopedia of Policy Studies, 43–69. Start Nagel.Google Scholar
Saez, T. M. M., Aronne, M. P., Caltana, L., and Brusco, A. H.. 2014. ‘Prenatal Exposure to the CB1 and CB2 Cannabinoid Receptor Agonist WIN 55,212-2 Alters Migration of Early-Born Glutamatergic Neurons and GABAergic Interneurons in the Rat Cerebral Cortex’. Journal of Neurochemistry 129 (4): 637–48.Google Scholar
Saffran, J. R. 2001. ‘Words in a Sea of Sounds: The Output of Infant Statistical Learning’. Cognition 81 (2): 149–69.Google Scholar
Sahu, J. K., Sharma, S., Kamate, M., et al. 2010. ‘Lead Encephalopathy in an Infant Mimicking a Neurometabolic Disorder’. Journal of Child Neurology 25 (3): 390–2.Google Scholar
Saigal, S., and Doyle, L. W.. 2008. ‘An Overview of Mortality and Sequelae of Preterm Birth from Infancy to Adulthood’. The Lancet 371 (9608): 261–9.Google Scholar
Saksida, A., Iannuzzi, S., Bogliotti, C., et al. 2016. ‘Phonological Skills, Visual Attention Span, and Visual Stress in Developmental Dyslexia’. Developmental Psychology 52 (10): 1503–16.Google Scholar
Sampaio-Baptista, C., and Johansen-Berg, H.. 2017. ‘White Matter Plasticity in the Adult Brain’. Neuron 96 (6): 1239–51.Google Scholar
Santhanam, P., Li, Z., Hu, X., Lynch, M. E., and Coles, C. D.. 2009. ‘Effects of Prenatal Alcohol Exposure on Brain Activation during an Arithmetic Task: An fMRI Study’. Alcoholism, Clinical and Experimental Research 33 (11): 1901–8.Google Scholar
Sarason, I. G. 1984. ‘Stress, Anxiety, and Cognitive Interference: Reactions to Tests’. Journal of Personality and Social Psychology 46 (4): 929–38.Google Scholar
Sarason, I. G. 1988. ‘Anxiety, Self-Preoccupation and Attention’. Anxiety Research 1 (1): 3–7.Google Scholar
Sasanguie, D., and Vos, H.. 2018. ‘About Why There Is a Shift from Cardinal to Ordinal Processing in the Association with Arithmetic between First and Second Grade’. Developmental Science 21 (5): e12653.Google Scholar
Sathian, K., Simon, T. J., Peterson, S., et al. 1999. ‘Neural Evidence Linking Visual Object Enumeration and Attention’. Journal of Cognitive Neuroscience 11 (1): 36–51.Google Scholar
Saygin, Z. M., Osher, D. E., Norton, E. S., et al. 2016. ‘Connectivity Precedes Function in the Development of the Visual Word Form Area’. Nature Neuroscience 19 (9): 1250–5.Google Scholar
Scheinost, D., Sinha, R., Cross, S. N., et al. 2017. ‘Does Prenatal Stress Alter the Developing Connectome?’ Pediatric Research 81 (1-2): 214–26.Google Scholar
Schel, M. A., and Klingberg, T.. 2017. ‘Specialization of the Right Intraparietal Sulcus for Processing Mathematics During Development’. Cerebral Cortex 27 (9): 4436–46.Google Scholar
Schiavone, G., Linkenkaer-Hansen, K, Maurits, N. M., et al. 2014. ‘Preliteracy Signatures of Poor-Reading Abilities in Resting-State EEG’. Frontiers in Human Neuroscience 8 (September): 735.Google Scholar
Schillinger, F. L., Vogel, S. E., Diedrich, J., and Grabner, R. H.. 2018. ‘Math Anxiety, Intelligence, and Performance in Mathematics: Insights from the German Adaptation of the Abbreviated Math Anxiety Scale (AMAS-G)’. Learning and Individual Differences 61 (January): 109–19.Google Scholar
Schleifer, P., and Landerl, K.. 2011. ‘Subitizing and Counting in Typical and Atypical Development’. Developmental Science 14 (2): 280–91.Google Scholar
Schlichting, M. L., Mumford, J. A., and Preston, A. R.. 2015. ‘Learning-Related Representational Changes Reveal Dissociable Integration and Separation Signatures in the Hippocampus and Prefrontal Cortex’. Nature Communications 6 (August): 8151.Google Scholar
Schmalz, X., Altoè, G., and Mulatti, C.. 2017. ‘Statistical Learning and Dyslexia: A Systematic Review’. Annals of Dyslexia 67 (2): 147–62.Google Scholar
Schneider, W. 2009. ‘The Development of Reading and Spelling: Relevant Precursors, Developmental Changes, and Individual Differences’. In Schneider, W. and Bullock, M. (eds.), Human development from early childhood to early adulthood: Findings from a 20 year longitudinal study, 199–220. Psychology Press.Google Scholar
Schneider, M., Beeres, K., Coban, L., et al. 2017. ‘Associations of Non-Symbolic and Symbolic Numerical Magnitude Processing with Mathematical Competence: A Meta-Analysis’. Developmental Science 20 (3): e12372. https://doi.org/10.1111/desc.12372.Google Scholar
Schneider, M., Merz, S., Stricker, J., et al. 2018. ‘Associations of Number Line Estimation with Mathematical Competence: A Meta-Analysis’. Child Development 89 (5): 1467–84.Google Scholar
Schneider, W., Roth, E., and Ennemoser, M.. 2000. ‘Training Phonological Skills and Letter Knowledge in Children at Risk for Dyslexia: A Comparison of Three Kindergarten Intervention Programs’. Journal of Educational Psychology 92 (2): 284–95. https://doi.org/10.1037/0022-0663.92.2.284.Google Scholar
Schneider, W., Blanke, I., Faust, V., Küspert, P. (2011). Würzburger Leise Leseprobe-Revision (WLLP-R). Hogrefe, GöttingenGoogle Scholar
Steinbrink, C., Klatte, M., & Lachmann, T. (2014). Phonological, temporal and spectral processing in vowel length discrimination is impaired in German primary school children with developmental dyslexia. Research in Developmental Disabilities, 35(11), 3034–3045. https://doi.org/10.1016/j.ridd.2014.07.049.Google Scholar
Schneps, M. H., Brockmole, J. R., Sonnert, G., and Pomplun, M.. 2012. ‘History of Reading Struggles Linked to Enhanced Learning in Low Spatial Frequency Scenes’. PloS One 7 (4): e35724.Google Scholar
Schneps, M. H., Thomson, J. M., Sonnert, G., et al. 2013. ‘Shorter Lines Facilitate Reading in Those Who Struggle’. PloS One 8 (8): e71161.Google Scholar
Schöneich, S., Kostarakos, K., and Hedwig, B.. 2015. ‘An Auditory Feature Detection Circuit for Sound Pattern Recognition’. Science Advances 1 (8): e1500325.Google Scholar
Schulte-Körne, G., Bartling, J., Deimel, W., and Remschmidt, H.. 2004. ‘Motion-Onset VEPs in Dyslexia. Evidence for Visual Perceptual Deficit’. Neuroreport 15 (6): 1075–8.Google Scholar
Schwartz, F., Epinat-Duclos, J., Léone, J., Poisson, A., and Prado, J.. 2018. ‘Impaired Neural Processing of Transitive Relations in Children with Math Learning Difficulty’. NeuroImage. Clinical 20 (October): 1255–65.Google Scholar
Schwartz, F., Epinat-Duclos, J., Léone, J., Poisson, A., and Prado, J. 2020. ‘Neural Representations of Transitive Relations Predict Current and Future Math Calculation Skills in Children’. Neuropsychologia 141 (April): 107410.Google Scholar
Schwartzman, A., Dougherty, R. F., and Taylor, J. E.. 2005. ‘Cross-Subject Comparison of Principal Diffusion Direction Maps’. Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine 53 (6): 1423–31.Google Scholar
Scientific Studies of Reading. 2020. 24 (1). www.tandfonline.com/toc/hssr20/24/1?nav=tocList.Google Scholar
Scott, J. A., Binns, C. W., Oddy, W. H., and Graham, K. I.. 2006. ‘Predictors of Breastfeeding Duration: Evidence from a Cohort Study’. Pediatrics 117 (4): e646–55.Google Scholar
Seidenberg, M. S., and McClelland, J. L.. 1989. ‘A Distributed, Developmental Model of Word Recognition and Naming’. Psychological Review 96 (4): 523–68.Google Scholar
Seipp, B. 1991. ‘Anxiety and Academic Performance: A Meta-Analysis of Findings’. Anxiety Research 4 (1): 27–41.Google Scholar
Sella, F., Berteletti, I., Lucangeli, D., and Zorzi, M.. 2016. ‘Spontaneous Non-Verbal Counting in Toddlers’. Developmental Science 19 (2): 329–37.Google Scholar
Semeraro, C., Giofrè, D., Coppola, G., Lucangeli, D., and Cassibba, R.. 2020. ‘The Role of Cognitive and Non-Cognitive Factors in Mathematics Achievement: The Importance of the Quality of the Student-Teacher Relationship in Middle School’. PloS One 15 (4): e0231381.Google Scholar
Serniclaes, W., Van Heghe, S., Mousty, P., Carré, R., and Sprenger-Charolles, L.. 2004. ‘Allophonic Mode of Speech Perception in Dyslexia’. Journal of Experimental Child Psychology 87 (4): 336–61.Google Scholar
Shafrir, U., and Siegel, L. S.. 1994. ‘Subtypes of Learning Disabilities in Adolescents and Adults’. Journal of Learning Disabilities. 27 (2): 123–4 https://doi.org/10.1177/002221949402700207.Google Scholar
Shalev, R. S., Manor, O., Kerem, B., et al. 2001. ‘Developmental Dyscalculia Is a Familial Learning Disability’. Journal of Learning Disabilities 34 (1): 59–65.Google Scholar
Share, D. L. 1995. ‘Phonological Recoding and Self-Teaching: Sine qua Non of Reading Acquisition’. Cognition 55 (2): 151–218; discussion 219–26.Google Scholar
Sharma, A., and Brody, A. L.. 2009. ‘In Vivo Brain Imaging of Human Exposure to Nicotine and Tobacco’. Handbook of Experimental Pharmacology, 192: 145–71.Google Scholar
Shaywitz, S. E., and Shaywitz, B. A.. 2008. Paying Attention to Reading: The Neurobiology of Reading and Dyslexia. Dev. Psychopathol. 20, 1329–49.Google Scholar
Shaywitz, B. A., Shaywitz, S. E., Blachman, B. A., et al. 2004. ‘Development of Left Occipitotemporal Systems for Skilled Reading in Children after a Phonologically- Based Intervention’. Biological Psychiatry 55 (9): 926–33.Google Scholar
Shaywitz, B. A., Shaywitz, S. E., Pugh, K. R., et al. 2002. ‘Disruption of Posterior Brain Systems for Reading in Children with Developmental Dyslexia’. Biological Psychiatry 52 (2): 101–10.Google Scholar
Sheffield, J. G., Raz, G, Sella, F., and Kadosh, R. Cohen. 2022. How Can Noise Alter Neurophysiology in Order to Improve Human Behaviour? A Combined Transcranial Random Noise Stimulation and Electroencephalography Study. bioRxiv 2020.01.09.900118; https://doi.org/10.1101/2020.01.09.900118.Google Scholar
Sheehan, M. C., Burke, T. A., Navas-Acien, A, et al. 2014. ‘Global Methylmercury Exposure from Seafood Consumption and Risk of Developmental Neurotoxicity: A Systematic Review’. Bulletin of the World Health Organization 92 (4): 254–69F.Google Scholar
Shohamy, D., and Wagner, A. D.. 2008. ‘Integrating Memories in the Human Brain: Hippocampal-Midbrain Encoding of Overlapping Events’. Neuron 60 (2): 378–89.Google Scholar
Shuey, E. A., & Kankaraš, M. 2018. ‘The Power and Promise of Early Learning’. OECD Education Working Papers, (186), 0_1-100.Google Scholar
Siddiqi, M. A.l, Laessig, R. H., and Reed, K. D.. 2003. ‘Polybrominated Diphenyl Ethers (PBDEs): New Pollutants-Old Diseases’. Clinical Medicine & Research 1 (4): 281–90.Google Scholar
Sie, L. T., van der Knaap, M. S., Oosting, J., et al. 2000. ‘MR Patterns of Hypoxic-Ischemic Brain Damage after Prenatal, Perinatal or Postnatal Asphyxia’. Neuropediatrics 31 (3): 128–36.Google Scholar
Siegler, R. S., and Shrager, J.. 1984. Strategy Choice in Addition and Subtraction: How do Children Know What to Do? In Sophian, C. (ed.), Origins of Cognitive Skills, 229–93. Erlbaum.Google Scholar
Silva, A. M., Júdice, P. B., Matias, C. N., et al. 2013. ‘Total Body Water and Its Compartments Are Not Affected by Ingesting a Moderate Dose of Caffeine in Healthy Young Adult Males’. Applied Physiology, Nutrition, and Metabolism = Physiologie Appliquee, Nutrition et Metabolisme 38 (6): 626–32.Google Scholar
SiMERR National Research Centre. 2021. QuickSmart - Narrowing the Achievement Gap. QuickSmart Overview 2021.Google Scholar
Simmons, F. R., and Singleton, C.. 2006. ‘The Mental and Written Arithmetic Abilities of Adults with Dyslexia’. Dyslexia 12 (2): 96–114.Google Scholar
Simms, V., Cragg, L., Gilmore, C., Marlow, N., and Johnson, S.. 2013. ‘Mathematics Difficulties in Children Born Very Preterm: Current Research and Future Directions’. Archives of Disease in Childhood: Fetal and Neonatal Edition 98 (5): F457–63.Google Scholar
Simms, V., Gilmore, C., Cragg, L., et al. 2015. ‘Nature and Origins of Mathematics Difficulties in Very Preterm Children: A Different Etiology than Developmental Dyscalculia’. Pediatric Research 77 (2): 389–95.Google Scholar
Simos, P. G., Fletcher, J. M., Sarkari, S., et al. 2007. ‘Intensive Instruction Affects Brain Magnetic Activity Associated with Oral Word Reading in Children with Persistent Reading Disabilities’. Journal of Learning Disabilities 40 (1): 37–48.Google Scholar
Siok, W. T., Perfetti, C. A., Jin, Z., and Tan, L. H.. 2004. ‘Biological Abnormality of Impaired Reading Is Constrained by Culture’. Nature 431 (7004): 71–6.Google Scholar
Sireteanu, R., Goebel, C., Goertz, R., et al. 2008. ‘Impaired Serial Visual Search in Children with Developmental Dyslexia’. Annals of the New York Academy of Sciences 1145 (December): 199–211.Google Scholar
Sirnes, E., Oltedal, L., Bartsch, H., et al. 2017. ‘Brain Morphology in School-Aged Children with Prenatal Opioid Exposure: A Structural MRI Study’. Early Human Development 106–7 (March): 33–9.Google Scholar
Sister Mary Fides Gough, O. P. 1954. ‘Why Failures in Mathematics? Mathemaphobia: Causes and Treatments’. The Clearing House: A Journal of Educational Strategies, Issues and Ideas 28 (5): 290–4.Google Scholar
Skagerlund, K., Bolt, T., Nomi, J. S., et al. 2019. ‘Disentangling Mathematics from Executive Functions by Investigating Unique Functional Connectivity Patterns Predictive of Mathematics Ability’. Journal of Cognitive Neuroscience 31 (4): 560–73.Google Scholar
Skagerlund, Kenny, and Träff, Ulf. 2016a. ‘Number Processing and Heterogeneity of Developmental Dyscalculia’. Journal of Learning Disabilities 49 (1): 36–50. https://doi.org/10.1177/0022219414522707.Google Scholar
Skagerlund, Kenny, and Träff, Ulf 2016b. ‘Number Processing and Heterogeneity of Developmental Dyscalculia: Subtypes With Different Cognitive Profiles and Deficits’. Journal of Learning Disabilities 49 (1): 36–50.Google Scholar
Skeide, M. A., Evans, T. M., Mei, E. Z., Abrams, D. A., and Menon, V.. 2018. ‘Neural Signatures of Co-Occurring Reading and Mathematical Difficulties’. Developmental Science 21 (6): e12680.Google Scholar
Skeide, M. A., and Friederici, A. D.. 2016. ‘The Ontogeny of the Cortical Language Network’. Nature Reviews. Neuroscience 17 (5): 323–32.Google Scholar
Skeide, M. A., Kirsten, H., Kraft, I., et al. 2015. ‘Genetic Dyslexia Risk Variant Is Related to Neural Connectivity Patterns Underlying Phonological Awareness in Children’. NeuroImage 118: 414–21. https://doi.org/10.1016/j.neuroimage.2015.06.024.Google Scholar
Skeide, M. A., Kraft, I, Muller, B., et al. 2016. ‘NRSN1 Associated Grey Matter Volume Profiles in the Visual Word Form Area Reveal Dyslexia before It Manifests Itself in School’. Brain: A Journal of Neurology 39 (10): 2792–803. https://doi.org/10.1093/brain/aww153.Google Scholar
Skeide, M. A., Kumar, U., Mishra, R. K., et al. 2017. ‘Learning to Read Alters Cortico-subcortical Cross-talk in the Visual System of Illiterates’. Science Advances 3 (5): e1602612.Google Scholar
Skeide, M. A., Wehrmann, K., Emami, Z., et al. 2020. ‘Neurobiological Origins of Individual Differences in Mathematical Ability’. PLOS Biology 18 (10): 24 (4): 387–400. https://doi.org/10.1371/journal.pbio.3000871.Google Scholar
Slot, E. M., van Viersen, S., de Bree, E. H., and Kroesbergen, E. H.. 2016. ‘Shared and Unique Risk Factors Underlying Mathematical Disability and Reading and Spelling Disability’. Frontiers in Psychology 7 (June): 803.Google Scholar
Smedt, B. De, Noël, M.-P., Gilmore, C., and Ansari, D.. 2013. ‘How Do Symbolic and Non-Symbolic Numerical Magnitude Processing Skills Relate to Individual Differences in Children’s Mathematical Skills? A Review of Evidence from Brain and Behavior’. Trends in Neuroscience and Education 2 (2): 48–55. https://doi.org/10.1016/j.tine.2013.06.001.Google Scholar
Smedt, B. De, Taylor, J., Archibald, L., and Ansari, D.. 2010. ‘How Is Phonological Processing Related to Individual Differences in Children’s Arithmetic Skills?’ Developmental Science 13 (3): 508–20. https://doi.org/10.1111/j.1467-7687.2009.00897.x.Google Scholar
Smit, D. J. A., Boomsma, D. I., Schnack, H. G., Hulshoff Pol, H. E., and de Geus, E. J. C. 2012. ‘Individual Differences in EEG Spectral Power Reflect Genetic Variance in Gray and White Matter Volumes’. Twin Research and Human Genetics: The Official Journal of the International Society for Twin Studies 15 (3): 384–92.Google Scholar
Smith, C. N., and Squire, L. R.. 2009. ‘Medial Temporal Lobe Activity during Retrieval of Semantic Memory Is Related to the Age of the Memory’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 29 (4): 930–8.Google Scholar
Smith, G. J., Booth, J. R., and McNorgan, C. 2018. ‘Longitudinal Task-Related Functional Connectivity Changes Predict Reading Development’. Frontiers in Psychology 9 (September): 1754.Google Scholar
Snowling, M. J., and Hayiou-Thomas, M. E.. 2006. ‘The Dyslexia Spectrum: Continuities between Reading, Speech, and Language Impairments’. Topics in Language Disorders 26 (2): 110.Google Scholar
Snowling, M. J., and Melby-Lervåg, M.. 2016. ‘Oral Language Deficits in Familial Dyslexia: A Meta-Analysis and Review’. Psychological Bulletin 142 (5): 498–545.Google Scholar
Sokolowski, H. M., Fias, W., Mousa, A., and Ansari, D.. 2017. ‘Common and Distinct Brain Regions in Both Parietal and Frontal Cortex Support Symbolic and Nonsymbolic Number Processing in Humans: A Functional Neuroimaging Meta-Analysis’. NeuroImage 146 (February): 376–94.Google Scholar
Solon, O., Riddell, T. J., Quimbo, S. A., et al. 2008. ‘Associations between Cognitive Function, Blood Lead Concentration, and Nutrition among Children in the Central Philippines’. The Journal of Pediatrics 152 (2): 237–43.Google Scholar
Soltanlou, M., Artemenko, C., Ehlis, A.-C., et al. 2018. ‘Reduction but No Shift in Brain Activation after Arithmetic Learning in Children: A Simultaneous fNIRS-EEG Study’. Scientific Reports 8: 1707. https://doi.org/10.1038/s41598-018-20007-x.Google Scholar
Soltész, F., Szűcs, D., Dékány, J., Márkus, A., and Csépe, V.. 2007. ‘A Combined Event-Related Potential and Neuropsychological Investigation of Developmental Dyscalculia’. Neuroscience Letters 417 (2): 181–6.Google Scholar
Song, S., Zhang, Y., Shu, H., Su, M., McBride, C.. 2020. ‘Universal and Specific Predictors of Chinese Children With Dyslexia: Exploring the Cognitive Deficits and Subtypes’. Front Psychol. 10: 2904. doi: 10.3389/fpsyg.2019.02904.Google Scholar
Soni, A., and Kumari, S.. 2017. ‘The Role of Parental Math Anxiety and Math Attitude in Their Children’s Math Achievement’. International Journal of Science and Mathematics Education 15 (2): 331–47.Google Scholar
Sonuga-Barke, E. J. S., Sergeant, J. A., Nigg, J., and Willcutt, E.. 2008. ‘Executive Dysfunction and Delay Aversion in Attention Deficit Hyperactivity Disorder: Nosologic and Diagnostic Implications’. Child and Adolescent Psychiatric Clinics of North America 17 (2): 367–84.Google Scholar
Sood, B., Delaney-Black, V., Covington, C., et al. 2001. ‘Prenatal Alcohol Exposure and Childhood Behavior at Age 6 to 7 Years: I. Dose-Response Effect’. Pediatrics 108 (2): E34.Google Scholar
Sowell, E. R., Lu, L. H., O’Hare, E. D., et al. 2007. ‘Functional Magnetic Resonance Imaging of Verbal Learning in Children with Heavy Prenatal Alcohol Exposure’. Neuroreport 18 (7): 635–9.Google Scholar
Spadoni, A. D., Bazinet, A. D., Fryer, S. L., et al. 2009. ‘BOLD Response during Spatial Working Memory in Youth with Heavy Prenatal Alcohol Exposure’. Alcoholism, Clinical and Experimental Research 33 (12): 2067–76.Google Scholar
Spencer, S. J., Steele, C. M., and Quinn, D. M.. 1999. ‘Stereotype Threat and Women’s Math Performance’. Journal of Experimental Social Psychology 35 (1): 4–28.Google Scholar
Sperling, A. J., Lu, Z.-L., Manis, F. R., and Seidenberg, M. S.. 2005. ‘Deficits in Perceptual Noise Exclusion in Developmental Dyslexia’. Nature Neuroscience 8 (7): 862–3.Google Scholar
Starr, A., DeWind, N. K., and Brannon, E. M.. 2017. ‘The Contributions of Numerical Acuity and Non-Numerical Stimulus Features to the Development of the Number Sense and Symbolic Math Achievement’. Cognition 168 (November): 222–33.Google Scholar
Starr, A., Libertus, M. E., and Brannon, E. M.. 2013. ‘Number Sense in Infancy Predicts Mathematical Abilities in Childhood’. Proceedings of the National Academy of Sciences of the United States of America 110 (45): 18116–20.Google Scholar
Staskal, D. F., Diliberto, J. J., and Birnbaum, L. S.. 2006. ‘Disposition of BDE 47 in Developing Mice’. Toxicological Sciences: An Official Journal of the Society of Toxicology 90 (2): 309–16.Google Scholar
Steckler, T., and Sahgal, A.. 1995. ‘The Role of Serotonergic-Cholinergic Interactions in the Mediation of Cognitive Behaviour’. Behavioural Brain Research 67 (2): 165–99.Google Scholar
Stein, John. 2014. ‘Dyslexia: The Role of Vision and Visual Attention’. Current Developmental Disorders Reports 1 (4): 267–80.Google Scholar
Stein, John 2019. ‘The Current Status of the Magnocellular Theory of Developmental Dyslexia’. Neuropsychologia 130 (July): 66–77.Google Scholar
Stein, J., and Walsh, V.. 1997. ‘To See but Not to Read; the Magnocellular Theory of Dyslexia’. Trends in Neurosciences 20 (4): 147–52.Google Scholar
Stewart, P., Fitzgerald, S., Reihman, J., et al. 2003. ‘Prenatal PCB Exposure, the Corpus Callosum, and Response Inhibition’. Environmental Health Perspectives 111 (13): 1670–7.Google Scholar
Stewart, P. W., Lonky, E., Reihman, J., et al. 2008. ‘The Relationship between Prenatal PCB Exposure and Intelligence (IQ) in 9-Year-Old Children’. Environmental Health Perspectives 116 (10): 1416–22.Google Scholar
Stigler, J. W. 1984. ‘“Mental Abacus”: The Effect of Abacus Training on Chinese Children’s Mental Calculation’. Cognitive Psychology 16 (2): 145–76.Google Scholar
Stinson, L. F., Payne, M. S., and Keelan, J. A.. 2018. ‘A Critical Review of the Bacterial Baptism Hypothesis and the Impact of Cesarean Delivery on the Infant Microbiome’. Frontiers of Medicine 5 (May): 135.Google Scholar
Stockholm Convention. n.d. ‘Guidance for the Inventory of PBDEs’. Accessed July 21, 2021a. http://chm.pops.int/Implementation/NIPs/Guidance/GuidancefortheinventoryofPBDEs/tabid/3171/Default.aspx.Google Scholar
Stockholm Convention n.d. ‘Stockholm Convention > Implementation > Industrial POPs > PCB > PCB Elimination Network > PEN Overview > Related Articles and Links > PCBs Info Exchange Platform’. Accessed July 21, 2021b. http://chm.pops.int/Default.aspx?tabid=3016.+Implementation+>+Industrial+POPs+>+PCB+>+PCB+Elimination+Network+>+PEN+Overview+>+Related+Articles+and+Links+>+PCBs+Info+Exchange+Platform’.+Accessed+July+21,+2021b.+http://chm.pops.int/Default.aspx?tabid=3016.>Google Scholar
Stoet, G., and Geary, D. C.. 2015. ‘Sex Differences in Academic Achievement Are Not Related to Political, Economic, or Social Equality’. Intelligence 48 (January): 137–51.Google Scholar
Stoianov, I. P., and Zorzi, M.. 2017. ‘Computational Foundations of the Visual Number Sense’. Behavioral and Brain Sciences 40: e191. https://doi.org/10.1017/s0140525x16002326.Google Scholar
Stoianov, I., and Zorzi, M.. 2012. ‘Emergence of a “Visual Number Sense” in Hierarchical Generative Models’. Nature Neuroscience 15 (2): 194–6.Google Scholar
Stoianov, I., Zorzi, M., and Umiltà, C.. 2004. ‘The Role of Semantic and Symbolic Representations in Arithmetic Processing: Insights from Simulated Dyscalculia in a Connectionist Model’. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior 40 (1): 194–6.Google Scholar
Stoll, B. J., Hansen, N. I., Adams-Chapman, I., et al. 2004. ‘Neurodevelopmental and Growth Impairment among Extremely Low-Birth-Weight Infants with Neonatal Infection’. JAMA: The Journal of the American Medical Association 292 (19): 2357–65.Google Scholar
Strand, S., Coulon, A. De, Meschi, E., et al. 2010. Drivers and Challenges in Raising the Achievement of Pupils from Bangladeshi, Somali and Turkish Backgrounds. Research Report DCSF-RR226. Department for Children School and Families.Google Scholar
Stromswold, K. 2001. ‘The Heritability of Language: A Review and Metaanalysis of Twin, Adoption, and Linkage Studies’. Language 77 (4): 647–723.Google Scholar
Strong, G. K., Torgerson, C. J., Torgerson, D., and Hulme, C.. 2011. ‘A Systematic Meta-Analytic Review of Evidence for the Effectiveness of the “Fast ForWord” Language Intervention Program’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 52 (3): 224–35.Google Scholar
Suinn, R. M., and Winston, E. H.. 2003. ‘The Mathematics Anxiety Rating Scale, a Brief Version: Psychometric Data’. Psychological Reports 92 (1): 167–73.Google Scholar
Suinn, R. M., Edie, C. A., Nicoletti, J., and Spinelli, P. R.. 1972. ‘The MARS, a Measure of Mathematics Anxiety: Psychometric Data’. Journal of Clinical Psychology 28 (3): 373–5.Google Scholar
Supekar, K., Iuculano, T., Chen, L., and Menon, V.. 2015. ‘Remediation of Childhood Math Anxiety and Associated Neural Circuits through Cognitive Tutoring’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 35 (36): 12574–83.Google Scholar
Supekar, K., Swigart, A. G., Tenison, C., et al. 2013. ‘Neural Predictors of Individual Differences in Response to Math Tutoring in Primary-Grade School Children’. Proceedings of the National Academy of Sciences of the United States of America 110 (20): 8230–5.Google Scholar
Sutskever, I., Vinyals, O., and Le, Q. V.. 2014. ‘Sequence to Sequence Learning with Neural Networks’. In Advances in Neural Information Processing Systems, edited by Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N., and Weinberger, K. Q.. Vol. 27. Curran Associates, Inc. https://proceedings.neurips.cc/paper/2014/file/a14ac55a4f27472c5d894ec1c3c743d2-Paper.pdf.Google Scholar
Suttie, M., Wetherill, L., Jacobson, S. W., et al. 2017. ‘Facial Curvature Detects and Explicates Ethnic Differences in Effects of Prenatal Alcohol Exposure’. Alcoholism, Clinical and Experimental Research 41 (8): 1471–83.Google Scholar
Sutton, E. F., Gilmore, L. A., Dunger, D. B., et al. 2016. ‘Developmental Programming: State-of-the-Science and Future Directions-Summary from a Pennington Biomedical Symposium’. Obesity 24 (5): 1018–26.Google Scholar
Sutton, R. S., and Barto, A. G.. 1998. ‘Reinforcement Learning: An Introduction’. IEEE Transactions on Neural Networks. https://doi.org/10.1109/tnn.1998.712192.Google Scholar
Sverrisson, F. A., Bateman, B. T., Aspelund, T., Skulason, S., and Zoega, H.. 2018. ‘Preeclampsia and Academic Performance in Children: A Nationwide Study from Iceland’. PloS One 13 (11): e0207884.Google Scholar
Swanson, H. L., Lee Swanson, H., and Jerman, O.. 2006. ‘Math Disabilities: A Selective Meta-Analysis of the Literature’. Review of Educational Research 76 (2): 249–74. https://doi.org/10.3102/00346543076002249.Google Scholar
Szczygieł, M. 2020. ‘When Does Math Anxiety in Parents and Teachers Predict Math Anxiety and Math Achievement in Elementary School Children? The Role of Gender and Grade Year’. Social Psychology of Education: An International Journal 23 (4): 1023–54.Google Scholar
Szkudlarek, E., and Brannon, E. M.. 2017. ‘Does the Approximate Number System Serve as a Foundation for Symbolic Mathematics?’ Language Learning and Development: The Official Journal of the Society for Language Development 13 (2): 171–90.Google Scholar
Szűcs, D. 2016. ‘Subtypes and Comorbidity in Mathematical Learning Disabilities’. Progress in Brain Research. 227: 277–304. https://doi.org/10.1016/bs.pbr.2016.04.027.Google Scholar
Szűcs, D., Devine, A., Soltesz, F., Nobes, A., and Gabriel, F.. 2013. ‘Developmental Dyscalculia Is Related to Visuo-Spatial Memory and Inhibition Impairment’. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior 49 (10): 2674–88.Google Scholar
Szűcs, D., Devine, A., Soltesz, F., Nobes, A., and Gabriel, F.. 2014. ‘Cognitive Components of a Mathematical Processing Network in 9-Year-Old Children’. Developmental Science 17 (4): 506–24.Google Scholar
Szűcs, D., and Goswami, U. 2013. ‘Developmental Dyscalculia: Fresh Perspectives’. Trends in Neuroscience and Education 2 (2): 33–7.Google Scholar
Szűcs, D., and Ioannidis, J. P. A.. 2017. ‘When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment’. Frontiers in Human Neuroscience 11 (August): 390.Google Scholar
Szűcs, D., and Mammarella, I. C.. 2020. ‘Math Anxiety. Educational Practices Series 31’. UNESCO International Bureau of Education. www.ibe.unesco.org/sites/default/files/resources/31_math_anxiety_web.pdf.Google Scholar
Takashima, A., Nieuwenhuis, I. L. C., Jensen, O., et al. 2009. ‘Shift from Hippocampal to Neocortical Centered Retrieval Network with Consolidation’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 29 (32): 10087–93.Google Scholar
Takeuchi, H., Taki, Y., Sassa, Y., et al. 2011. ‘Working Memory Training Using Mental Calculation Impacts Regional Gray Matter of the Frontal and Parietal Regions’. PloS One 6 (8): e23175.Google Scholar
Tallal, P. 1980. ‘Auditory Temporal Perception, Phonics, and Reading Disabilities in Children’. Brain and Language 9 (2): 182–98. https://doi.org/10.1016/0093-934x(80)90139-x.Google Scholar
Tallal, P 2004. ‘Improving Language and Literacy Is a Matter of Time’. Nature Reviews. Neuroscience 5 (9): 721–8.Google Scholar
Tallal, P., and Piercy, M.. 1973. ‘Defects of Non-Verbal Auditory Perception in Children with Developmental Aphasia’. Nature 241 (5390): 468–9.Google Scholar
Tanaka, J. W., and Curran, T.. 2001. ‘A Neural Basis for Expert Object Recognition’. Psychological Science 12 (1): 43–7.Google Scholar
Tanda, R., Salsberry, P. J., Reagan, P. B., and Fang, M. Z.. 2013. ‘The Impact of Prepregnancy Obesity on Children’s Cognitive Test Scores’. Maternal and Child Health Journal 17 (2): 222–9.Google Scholar
Taylor, J., Roehrig, A. D., Soden Hensler, B., Connor, C. M., and Schatschneider, C.. 2010. ‘Teacher Quality Moderates the Genetic Effects on Early Reading’. Science 328 (5977): 512–14.Google Scholar
Taylor, J. S. H., Davis, M. H., and Rastle, Kathleen. 2019. ‘Mapping Visual Symbols onto Spoken Language along the Ventral Visual Stream’. Proceedings of the National Academy of Sciences of the United States of America 116 (36): 17723–8.Google Scholar
Temple, E., Deutsch, G. K., Poldrack, R. A., et al. 2003. ‘Neural Deficits in Children with Dyslexia Ameliorated by Behavioral Remediation: Evidence from Functional MRI’. Proceedings of the National Academy of Sciences of the United States of America 100 (5): 2860–5.Google Scholar
Temple, J. L., Bernard, C, Lipshultz, S. E., et al. 2017. ‘The Safety of Ingested Caffeine: A Comprehensive Review’. Frontiers in Psychiatry/Frontiers Research Foundation 8 (May): 80.Google Scholar
Tenison, C., Fincham, J. M., and Anderson, J. R.. 2014. ‘Detecting Math Problem Solving Strategies: An Investigation into the Use of Retrospective Self-Reports, Latency and fMRI Data’. Neuropsychologia 54 (February): 41–52.Google Scholar
Terplan, M., Smith, E. J., Kozloski, M. J., and Pollack, H. A.. 2009. ‘Methamphetamine Use among Pregnant Women’. Obstetrics and Gynecology 113 (6): 1285–91.Google Scholar
Testolin, A. 2020. ‘The Challenge of Modeling the Acquisition of Mathematical Concepts’. Frontiers in Human Neuroscience 14 (March): 100.Google Scholar
Testolin, A., Dolfi, S., Rochus, M., and Zorzi, M. (2020a). ‘Visual sense of number vs. sense of magnitude in humans and machines’. Scientific Reports, 10(1), 1 –13.Google Scholar
Testolin, A., Stoianov, I., De Filippo De Grazia, M, and Zorzi, M.. 2013. ‘Deep Unsupervised Learning on a Desktop PC: A Primer for Cognitive Scientists’. Frontiers in Psychology 4 (May): 251.Google Scholar
Testolin, A., Stoianov, I., Sperduti, A., and Zorzi, M.. 2016. ‘Learning Orthographic Structure With Sequential Generative Neural Networks’. Cognitive Science 40 (3): 579–606.Google Scholar
Testolin, A., Stoianov, I., and Zorzi, M.. 2017. ‘Letter Perception Emerges from Unsupervised Deep Learning and Recycling of Natural Image Features’. Nature Human Behaviour 1 (9): 657–64.Google Scholar
Testolin, A., and Zorzi, M.. 2016. ‘Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions’. Frontiers in Computational Neuroscience 10 (July): 73.Google Scholar
Testolin, A., Zou, W. Y., and McClelland, J. L.. 2020b. ‘Numerosity Discrimination in Deep Neural Networks: Initial Competence, Developmental Refinement and Experience Statistics’. Developmental Science 23 (5): e12940.Google Scholar
Thomas, M. S. C., Fedor, A., Davis, R., et al. 2019. ‘Computational Modeling of Interventions for Developmental Disorders’. Psychological Review 126 (5): 693–726.Google Scholar
Thomas, M. S. C., and Karmiloff-Smith, A.. 2003. ‘Modeling Language Acquisition in Atypical Phenotypes’. Psychological Review 110 (4): 647–82.Google Scholar
Thompson, Paul A., Charles Hulme, Hannah M. Nash, , et al. 2015. ‘Developmental Dyslexia: Predicting Individual Risk’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 56 (9): 976–87.Google Scholar
Tiffany-Castiglioni, E. 1993. ‘Cell Culture Models for Lead Toxicity in Neuronal and Glial Cells’. Neurotoxicology 14 (4): 513–36.Google Scholar
Toll, S. W. M., Kroesbergen, E. H., and Van, J. E. H. Luit, . 2016. ‘Visual Working Memory and Number Sense: Testing the Double Deficit Hypothesis in Mathematics’. The British Journal of Educational Psychology 86 (3): 429–45.Google Scholar
Toll, S. W. M., Van der Ven, S. H. G., Kroesbergen, E. H., and Van Luit, J. E. H.. 2011. ‘Executive Functions as Predictors of Math Learning Disabilities’. Journal of Learning Disabilities 44 (6): 521–32.Google Scholar
Tompary, A., and Davachi, L.. 2017. ‘Consolidation Promotes the Emergence of Representational Overlap in the Hippocampus and Medial Prefrontal Cortex’. Neuron 96 (1): 228–41.Google Scholar
Torppa, M., Georgiou, G. K., Niemi, P., Lerkkanen, M.-K., and Poikkeus, A.-M.. 2017. ‘The Precursors of Double Dissociation between Reading and Spelling in a Transparent Orthography’. Annals of Dyslexia 67: 42–62. https://doi.org/10.1007/s11881-016-0131-5.Google Scholar
Torre, G. A., Matejko, A. A., and Eden, G. F.. 2020. ‘The Relationship between Brain Structure and Proficiency in Reading and Mathematics in Children, Adolescents, and Emerging Adults’. Developmental Cognitive Neuroscience 45 (October): 100856.Google Scholar
Toth, G., and Siegel., L. S. 1994. ‘A Critical Evaluation of the IQ-Achievement Discrepancy Based Definition of Dyslexia’. In van den Bos, K. P., Siegel, L. S., Bakker, D. J., and Share, D. L. (eds.), Current Directions in Dyslexia Research, 45–70. Swets & Zeitlinger Publishers.Google Scholar
Traccis, F., Frau, R., and Melis, M.. 2020. ‘Gender Differences in the Outcome of Offspring Prenatally Exposed to Drugs of Abuse’. Frontiers in Behavioral Neuroscience 14 (June): 72.Google Scholar
Travis, K. E., Adams, J. N., Ben-Shachar, M., and Feldman, H. M.. 2015. ‘Decreased and Increased Anisotropy along Major Cerebral White Matter Tracts in Preterm Children and Adolescents’. PloS One 10 (11): e0142860.Google Scholar
Travis, K. E., Ben-Shachar, M, Myall, N. J., and Feldman, H. M.. 2016. ‘Variations in the Neurobiology of Reading in Children and Adolescents Born Full Term and Preterm’. NeuroImage. Clinical 11 (April): 555–65.Google Scholar
Trope, I., Lopez-Villegas, D., and Lenkinski, R. E.. 1998. ‘Magnetic Resonance Imaging and Spectroscopy of Regional Brain Structure in a 10-Year-Old Boy with Elevated Blood Lead Levels’. Pediatrics 101 (6): E7.Google Scholar
Tsai, C. L., Jang, T. H., and Wang, L. H.. 1995. ‘Effects of Mercury on Serotonin Concentration in the Brain of Tilapia, Oreochromis Mossambicus’. Neuroscience Letters 184 (3): 208–11.Google Scholar
Tschentscher, N., Hauk, O, Fischer, M. H., and Pulvermüller, F.. 2012. ‘You Can Count on the Motor Cortex: Finger Counting Habits Modulate Motor Cortex Activation Evoked by Numbers’. NeuroImage 59 (4): 3139–48.Google Scholar
Tsolaki, A., Kosmidou, V., Hadjileontiadis, L., Kompatsiaris, I. Y., and Tsolaki, M.. 2015. ‘Brain Source Localization of MMN, P300 and N400: Aging and Gender Differences’. Brain Research 1603 (April): 32–49.Google Scholar
Tucker-Drob, E. M. 2017. ‘Motivational Factors as Mechanisms of Gene-Environment Transactions in Cognitive Development and Academic Achievement’. In Elliot, A. J, Dweck, C. S, and Yeager, D. S (eds.), Handbook of Competence and Motivation: Theory and Application, 471–86. Guilford Press.Google Scholar
Tucker-Drob, E. M., and Paige Harden, K.. 2012. ‘Intellectual Interest Mediates Gene × Socioeconomic Status Interaction on Adolescent Academic Achievement’. Child Development 83 (2): 743–57.Google Scholar
Twilhaar, E. S., de Kieviet, J. F., Aarnoudse-Moens, C. S, van Elburg, R. M., and Oosterlaan, J.. 2018. ‘Academic Performance of Children Born Preterm: A Meta-Analysis and Meta-Regression’. Archives of Disease in Childhood. Fetal and Neonatal Edition 103 (4): F322–30.Google Scholar
Ulfarsson, M. O., Walters, G. B., Gustafsson, O., et al. 2017. ‘15q11.2 CNV Affects Cognitive, Structural and Functional Correlates of Dyslexia and Dyscalculia’. Translational Psychiatry 7: e1109. https://doi.org/10.1038/tp.2017.77.Google Scholar
Undeman, E., Brown, T. N., McLachlan, M. S., and Wania, F.. 2018. ‘Who in the World Is Most Exposed to Polychlorinated Biphenyls? Using Models to Identify Highly Exposed Populations’. Environmental Research Letters: ERL [Web Site] 13 (6): 064036.Google Scholar
UNICEF Canada. 2016. Child Development & Education. www.unicef.ca/en/discover/educationGoogle Scholar
United Nations (UN). 2007. Convention on the Rights of Persons with Disabilities.Google Scholar
United Nations Office on Drugs and Crime. 2013. ‘World Drug Report 2013’. World Drug Report. www.unodc.org/doc/wdr2013/World_Drug_Report_2013.pdf. https://doi.org/10.18356/d30739c2-en.Google Scholar
Vaaga, C. E., Brown, S. T., and Raman, I. M.. 2020. ‘Cerebellar Modulation of Synaptic Input to Freezing-Related Neurons in the Periaqueductal Gray’. eLife 9 (March). https://doi.org/10.7554/eLife.54302.Google Scholar
Valdois, S., Bosse, M.-L., and Tainturier, M.-J.. 2004. ‘The Cognitive Deficits Responsible for Developmental Dyslexia: Review of Evidence for a Selective Visual Attentional Disorder’. Dyslexia 10 (4): 339–63.Google Scholar
Valdois, S., Lassus-Sangosse, D., and Lobier, M. 2012. ‘Impaired Letter-String Processing in Developmental Dyslexia: What Visual-to-Phonology Code Mapping Disorder?’ Dyslexia 18 (2): 77–93.Google Scholar
Vanbinst, K., Bellon, E., and Dowker, A.. 2020. ‘Mathematics Anxiety: An Intergenerational Approach’. Frontiers in Psychology 11 (July): 1648.Google Scholar
van Bergen, E., de Jong, P. F. de, Maassen, B., & van der Leij, A. (2014). The effect of parents’ literacy skills and children’s preliteracy skills on the risk of dyslexia. Journal of Abnormal Child Psychology, 42(7), 1187–1200. https://doi.org/10.1007/s10802-014-9858-9.Google Scholar
van Bueren, N. E. R., Reed, T. L., Nguyen, V., et al. 2021Personalized Brain Stimulation for Effective Neurointervention Across Participants. PLOS Computational Biology 17 (9): e1008886. https://doi.org/10.1371/journal.pcbi.1008886.Google Scholar
van Bueren, N. E. R., van der Ven, S. H. G., Roelofs, K., Cohen Kadosh, R., and Kroesbergen, E. H.. 2022. Predicting Math Ability using Working Memory, Number Sense, and Neurophysiology in Children and Adults. bioRxiv 2022.02.10.479865; https://doi.org/10.1101/2022.02.10.479865.Google Scholar
Van den Bergh, B. R. H., van den Heuvel, M. I, Lahti, M., et al. 2020. ‘Prenatal Developmental Origins of Behavior and Mental Health: The Influence of Maternal Stress in Pregnancy’. Neuroscience and Biobehavioral Reviews 117 (October): 26–64.Google Scholar
Vanderauwera, J., Wouters, J., Vandermosten, M., and Ghesquière, P.. 2017. ‘Early Dynamics of White Matter Deficits in Children Developing Dyslexia’. Developmental Cognitive Neuroscience 27 (October): 69–77.Google Scholar
Vandermosten, M., Boets, B., Luts, H., et al. 2010. ‘Adults with Dyslexia Are Impaired in Categorizing Speech and Nonspeech Sounds on the Basis of Temporal Cues’. Proceedings of the National Academy of Sciences of the United States of America 107 (23): 10389–94.Google Scholar
Vandermosten, M., Boets, B., Poelmans, H., et al. 2012. ‘A Tractography Study in Dyslexia: Neuroanatomic Correlates of Orthographic, Phonological and Speech Processing’. Brain: A Journal of Neurology 135 (3): 935–48.Google Scholar
Vandermosten, M., Boets, B., Wouters, J., and Pol, G. 2012. ‘A Qualitative and Quantitative Review of Diffusion Tensor Imaging Studies in Reading and Dyslexia’. Neuroscience and Biobehavioral Reviews 36 (6): 1532–52.Google Scholar
Vandermosten, M., Correia, J., Vanderauwera, J., et al. 2019. ‘Brain Activity Patterns of Phonemic Representations Are Atypical in Beginning Readers with Family Risk for Dyslexia’. Developmental Science, April: e12857.Google Scholar
Vandermosten, M., Vanderauwera, J., Theys, C., et al. 2015. ‘A DTI Tractography Study in Pre-Readers at Risk for Dyslexia’. Developmental Cognitive Neuroscience 14: 8–15.Google Scholar
Van Hirtum, T., Ghesquière, P., and Wouters, J.. 2021. ‘A Bridge over Troubled Listening: Improving Speech-in-Noise Perception by Children with Dyslexia’. Journal of the Association for Research in Otolaryngology: JARO, April. https://doi.org/10.1007/s10162-021-00793-4.Google Scholar
Van Hirtum, T., Moncada-Torres, A., Ghesquière, P., and Wouters, J.. 2019. ‘Speech Envelope Enhancement Instantaneously Effaces Atypical Speech Perception in Dyslexia’. Ear and Hearing 40 (5): 1242–52.Google Scholar
Vanvooren, S., Poelmans, H., Hofmann, M., Ghesquière, P., and Wouters, J.. 2014. ‘Hemispheric Asymmetry in Auditory Processing of Speech Envelope Modulations in Prereading Children’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 34 (4): 1523–9.Google Scholar
Vatansever, G., Üstün, S., Ayyıldız, N., and Çiçek, M.. 2020. ‘Developmental Alterations of the Numerical Processing Networks in the Brain’. Brain and Cognition 141 (June): 105551.Google Scholar
Veena, S. R., Gale, C. R., Krishnaveni, G. V., et al. 2016. ‘Association between Maternal Nutritional Status in Pregnancy and Offspring Cognitive Function during Childhood and Adolescence; a Systematic Review’. BMC Pregnancy and Childbirth 16 (August): 220.Google Scholar
Vellutino, F. R., Fletcher, J. M., Snowling, M. J., and Scanlon, D. M.. 2004. ‘Specific Reading Disability (Dyslexia): What Have We Learned in the Past Four Decades?’ Journal of Child Psychology and Psychiatry, and Allied Disciplines 45 (1): 2–40.Google Scholar
Verguts, T., and Fias, W.. 2004. ‘Representation of Number in Animals and Humans: A Neural Model’. Journal of Cognitive Neuroscience 16 (9): 1493–504.Google Scholar
Verhoeven, L., Perfetti, C., and Pugh, K.. 2019. Developmental Dyslexia across Languages and Writing Systems. Cambridge University Press.Google Scholar
Verhoeven, L., Nag, S., Perfetti, C. A., and Pugh, K. (eds.). 2022. Global Variation of Literacy Development. Cambridge University Press.Google Scholar
Victora, C. G., Bahl, R., Barros, A. J. D., et al. 2016. ‘Breastfeeding in the 21st Century: Epidemiology, Mechanisms, and Lifelong Effect’. The Lancet 387 (10017): 475–90.Google Scholar
Victora, C. G., Barros, F. C., Horta, B. L., and Lima, R. C.. 2005. ‘Breastfeeding and School Achievement in Brazilian Adolescents’. Acta Paediatrica 94 (11): 1656–60.Google Scholar
Vidyasagar, T. R., and Pammer, K.. 2010. ‘Dyslexia: A Deficit in Visuo-Spatial Attention, Not in Phonological Processing’. Trends in Cognitive Sciences 14 (2): 57–63.Google Scholar
Visscher, A. De, Noël, M.-P., Pesenti, M., and Dormal, V.. 2018. ‘Developmental Dyscalculia in Adults: Beyond Numerical Magnitude Impairment’. Journal of Learning Disabilities 51 (6): 600–11. https://doi.org/10.1177/0022219417732338.Google Scholar
Vogel, E. K., and Luck, S. J.. 2000. ‘The Visual N1 Component as an Index of a Discrimination Process’. Psychophysiology 37 (2): 190–203.Google Scholar
Vogel, S. E., Goffin, C., and Ansari, D.. 2015. ‘Developmental Specialization of the Left Parietal Cortex for the Semantic Representation of Arabic Numerals: An fMR-Adaptation Study’. Developmental Cognitive Neuroscience 12 (April): 61–73.Google Scholar
Volpe, J. J. 2009. ‘Brain Injury in Premature Infants: A Complex Amalgam of Destructive and Developmental Disturbances’. Lancet Neurology 8 (1): 110–24.Google Scholar
von Aster, M., Kaufman, A. S., McCaskey, U. and K. Kucian, K. (in press). Rechenstörungen im Kindes- und Jugendalter. In Fegert, J. et al. (eds.), Psychiatrie und Psychotherapie des Kindes- und Jugendalters. Heidelberg: Springer.Google Scholar
Vukovic, R. K., and Lesaux, N. K.. 2013. ‘The Language of Mathematics: Investigating the Ways Language Counts for Children’s Mathematical Development’. Journal of Experimental Child Psychology 115 (2): 227–44. https://doi.org/10.1016/j.jecp.2013.02.002.Google Scholar
Vuokko, E., Niemivirta, M., and Helenius, P.. 2013. ‘Cortical Activation Patterns during Subitizing and Counting’. Brain Research 1497 (February): 40–52.Google Scholar
Wachinger, C., Volkmer, S., Bublath, K., et al. 2018. ‘Does the Late Positive Component Reflect Successful Reading Acquisition? A Longitudinal ERP Study’. NeuroImage. Clinical 17: 232–40.Google Scholar
Wakschlag, L. S., Pickett, K. E., Cook, E. Jr, Benowitz, N. L., and Leventhal, B. L.. 2002. ‘Maternal Smoking during Pregnancy and Severe Antisocial Behavior in Offspring: A Review’. American Journal of Public Health 92 (6): 966–74.Google Scholar
Walfisch, A., Sermer, C., Cressman, A., and Koren, G.. 2013. ‘Breast Milk and Cognitive Development–the Role of Confounders: A Systematic Review’. BMJ Open 3 (8): e003259.Google Scholar
Walhovd, K. B., Moe, V., Slinning, K., et al. 2007. ‘Volumetric Cerebral Characteristics of Children Exposed to Opiates and Other Substances in Utero’. NeuroImage 36 (4): 1331–44.Google Scholar
Walhovd, K. B., Westlye, L. T., Moe, V., et al. 2010. ‘White Matter Characteristics and Cognition in Prenatally Opiate- and Polysubstance-Exposed Children: A Diffusion Tensor Imaging Study’. AJNR. American Journal of Neuroradiology 31 (5): 894–900.Google Scholar
Walhovd, K. B., Watts, R., Amlien, I., and Woodward, L. J.. 2012. ‘Neural Tract Development of Infants Born to Methadone-Maintained Mothers’. Pediatric Neurology 47 (1): 1–6.Google Scholar
Walker, A., Rosenberg, M., and Balaban-Gil, K.. 1999. ‘Neurodevelopmental and Neurobehavioral Sequelae of Selected Substances of Abuse and Psychiatric Medications in Utero’. Child and Adolescent Psychiatric Clinics of North America 8 (4): 845–67.Google Scholar
Walsh, V. 2003. ‘A Theory of Magnitude: Common Cortical Metrics of Time, Space and Quantity’. Trends in Cognitive Sciences 7 (11): 483–8.Google Scholar
Wandell, B. A., Rauschecker, A. M., and Yeatman, J. D.. 2012. ‘Learning to See Words’. Annual Review of Psychology 63 (6): 31–53.Google Scholar
Wandell, B. A., and Smirnakis, S. M.. 2009. ‘Plasticity and Stability of Visual Field Maps in Adult Primary Visual Cortex’. Nature Reviews. Neuroscience 10 (12): 873–4.Google Scholar
Wandell, B. A., and Yeatman, J. D.. 2013. ‘Biological Development of Reading Circuits’. Current Opinion in Neurobiology 23 (2): 261–8.Google Scholar
Wang, F., Karipidis, I. I., Pleisch, G., Fraga-González, G., and Brem, S.. 2020. ‘Development of Print-Speech Integration in the Brain of Beginning Readers With Varying Reading Skills’. Frontiers in Human Neuroscience 14 (August): 289.Google Scholar
Wang, Y., Mauer, M. V., Raney, T., et al. 2016. ‘Development of Tract-Specific White Matter Pathways During Early Reading Development in At-Risk Children and Typical Controls’. Cerebral Cortex, April: bhw095.Google Scholar
Wang, Y., Mauer, M. V., Raney, T., et al. 2017. Development of Tract-Specific White Matter Pathways During Early Reading Development in At-Risk Children and Typical Controls. Cereb Cortex. 27 (4): 2469–85.Google Scholar
Warner, T. D., Roussos-Ross, D., and Behnke, M.. 2014. ‘It’s Not Your Mother’s Marijuana: Effects on Maternal-Fetal Health and the Developing Child’. Clinics in Perinatology 41 (4): 877–94.Google Scholar
Water, E. de, Curtin, P., Zilverstand, A., et al. 2019. ‘A Preliminary Study on Prenatal Polybrominated Diphenyl Ether Serum Concentrations and Intrinsic Functional Network Organization and Executive Functioning in Childhood’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 60 (9): 1010–20.Google Scholar
Weiner, E. R. 2008. Applications of Environmental Aquatic Chemistry: A Practical Guide, Second Edition. 2nd ed. CRC Press. https://doi.org/10.1201/9781420008371.Google Scholar
Weinstock, M. 2005. ‘The Potential Influence of Maternal Stress Hormones on Development and Mental Health of the Offspring’. Brain, Behavior, and Immunity 19 (4): 296–308.Google Scholar
Weiskopf, N., Mohammadi, S., Lutti, A., and Callaghan, M. F.. 2015. ‘Advances in MRI-Based Computational Neuroanatomy: From Morphometry to in-Vivo Histology’. Current Opinion in Neurology 28 (4): 313–22.Google Scholar
Wenger, E., Brozzoli, C., Lindenberger, U., and Lövdén, M.. 2017. ‘Expansion and Renormalization of Human Brain Structure During Skill Acquisition’. Trends in Cognitive Sciences 21 (12): 930–9.Google Scholar
Werker, J. F., and Hensch, T. K.. 2014. ‘Critical Periods in Speech Perception: New Directions’. Annual Review of Psychology 66 (September): 1–24.Google Scholar
Westmark, C. J. 2013. ‘Soy Infant Formula May Be Associated with Autistic Behaviors’. Autism-Open Access 3 (November). https://doi.org/10.4172/2165-7890.1000120.Google Scholar
Wever, R., and Runia, T. F. H.. 2018. ‘Subitizing with Variational Autoencoders’. arXiv [cs.CV]. arXiv. http://arxiv.org/abs/1808.00257.Google Scholar
White, R. F., Palumbo, C. L., Yurgelun-Todd, D. A., et al. 2011. ‘Functional MRI Approach to Developmental Methylmercury and Polychlorinated Biphenyl Neurotoxicity’. Neurotoxicology 32 (6): 975–80.Google Scholar
White, T., Su, S., Schmidt, M., Kao, C.-Y., and Sapiro, G.. 2010. ‘The Development of Gyrification in Childhood and Adolescence’. Brain and Cognition 72 (1): 36–45.Google Scholar
Whitney, D., and Levi, D. M.. 2011. ‘Visual Crowding: A Fundamental Limit on Conscious Perception and Object Recognition’. Trends in Cognitive Sciences 15 (4): 160–8.Google Scholar
Wigfield, A., Eccles, J. S., Mac, D. Iver, D. A. Reuman, and Carol Midgley, . 1991. ‘Transitions during Early Adolescence: Changes in Children’s Domain-Specific Self-Perceptions and General Self-Esteem across the Transition to Junior High School’. Developmental Psychology 27 (4): 552–65.Google Scholar
Wigfield, A., and Meece, J. L.. 1988. ‘Math Anxiety in Elementary and Secondary School Students’. Journal of Educational Psychology 80 (2): 210–16.Google Scholar
Wiggs, K. K., Rickert, M. E., Hernandez-Diaz, S., et al. 2017. ‘A Family-Based Study of the Association between Labor Induction and Offspring Attention-Deficit Hyperactivity Disorder and Low Academic Achievement’. Behavior Genetics 47 (4): 383–93.Google Scholar
Wijngaarden, E. van, Myers, G. J., Thurston, S. W., Shamlaye, C. F., and Davidson, P. W.. 2009. ‘Interpreting Epidemiological Evidence in the Presence of Multiple Endpoints: An Alternative Analytic Approach Using the 9-Year Follow-up of the Seychelles Child Development Study’. International Archives of Occupational and Environmental Health 82 (8): 1031–41.Google Scholar
Wilcke, A., Ligges, C., Burkhardt, J., et al. 2012. ‘Imaging Genetics of FOXP2 in Dyslexia’. European Journal of Human Genetics: EJHG 20 (2): 224–9.Google Scholar
Wilkey, E. D., Cutting, L. E., and Price, G. R.. 2018. ‘Neuroanatomical Correlates of Performance in a State-Wide Test of Math Achievement’. Developmental Science 21 (2): e12545. https://doi.org/10.1111/desc.12545.Google Scholar
Wilkey, E. D., Pollack, C., and Price, G. R.. 2020. ‘Dyscalculia and Typical Math Achievement Are Associated with Individual Differences in Number-Specific Executive Function’. Child Development 91 (2): 596–619.Google Scholar
Willburger, E., Fussenegger, B., Moll, K., Wood, G., and Landerl, K.. 2008. ‘Naming Speed in Dyslexia and Dyscalculia’. Learning and Individual Differences 18 (2): 224–36.Google Scholar
Willcutt, E. G., McGrath, L. M., Pennington, B. F., et al. 2019. ‘Understanding Comorbidity between Specific Learning Disabilities’. New Directions for Child and Adolescent Development 2019 (165): 91–109.Google Scholar
Willcutt, E. G., Pennington, B. F., Duncan, L., et al. 2010. ‘Understanding the Complex Etiologies of Developmental Disorders: Behavioral and Molecular Genetic Approaches’. Journal of Developmental and Behavioral Pediatrics: JDBP 31 (7): 533–44.Google Scholar
Willcutt, E. G., Petrill, S. A., Wu, S., et al. 2013. ‘Comorbidity between Reading Disability and Math Disability: Concurrent Psychopathology, Functional Impairment, and Neuropsychological Functioning’. Journal of Learning Disabilities 46 (6): 500–16.Google Scholar
Williams, G. R. 2008. ‘Neurodevelopmental and Neurophysiological Actions of Thyroid Hormone’. Journal of Neuroendocrinology 20 (6): 784–94.Google Scholar
Willoughby, K. A., Sheard, E. D., Nash, K., and Rovet, J.. 2008. ‘Effects of Prenatal Alcohol Exposure on Hippocampal Volume, Verbal Learning, and Verbal and Spatial Recall in Late Childhood’. Journal of the International Neuropsychological Society: JINS 14 (6): 1022–33.Google Scholar
Wilson, A. J., Andrewes, S. G., Struthers, H, et al. 2015. ‘Dyscalculia and Dyslexia in Adults: Cognitive Bases of Comorbidity’. Learning and Individual Differences 37 (January): 118–32.Google Scholar
Wimmer, H. 1993. ‘Characteristics of Developmental Dyslexia in a Regular Writing System’. Applied Psycholinguistics 14 (1): 1–33.Google Scholar
Wimmer, H., and Mayringer, H.. 2002. ‘Dysfluent Reading in the Absence of Spelling Difficulties: A Specific Disability in Regular Orthographies’. Journal of Educational Psychology 94 (2): 227–77. https://doi.org/10.1037/0022-0663.94.2.272.Google Scholar
Wimmer, H., and Schurz, M.. 2010. ‘Dyslexia in Regular Orthographies: Manifestation and Causation’. Dyslexia 16 (4): 283–99.Google Scholar
Wise Younger, J., Tucker-Drob, E., and Booth, J. R.. 2017. ‘Longitudinal Changes in Reading Network Connectivity Related to Skill Improvement’. NeuroImage 158 (September): 90–8.Google Scholar
Wittmann, E., and Müller, G.. 2012. Das Zahlenbuch. Klett.Google Scholar
Wong, P. W., Brackney, W. R., and Pessah, I. N.. 1997. ‘Ortho-Substituted Polychlorinated Biphenyls Alter Microsomal Calcium Transport by Direct Interaction with Ryanodine Receptors of Mammalian Brain’. The Journal of Biological Chemistry 272 (24): 15145–53.Google Scholar
Wood, L, Egger, M., Gluud, L. L., et al. 2008. Empirical Evidence of Bias in Treatment Effect Estimates in Controlled Trials with Different Interventions and Outcomes: Meta-Epidemiological Study. BMJ 336 (7644): 601–5.Google Scholar
Woodruff Carr, K., White-Schwoch, T., Tierney, A. T., Strait, D. L., and Kraus, N.. 2014. ‘Beat Synchronization Predicts Neural Speech Encoding and Reading Readiness in Preschoolers’. Proceedings of the National Academy of Sciences of the United States of America 111 (40): 14559–64.Google Scholar
Woody, C. A., Ferrari, A. J., Siskind, D. J., Whiteford, H. A., and Harris, M. G.. 2017. ‘A Systematic Review and Meta-Regression of the Prevalence and Incidence of Perinatal Depression’. Journal of Affective Disorders 219 (September): 86–92.Google Scholar
World Health Organization. n.d. ‘Breastfeeding’. n.d. Accessed July 13, 2021a. www.who.int/news-room/facts-in-pictures/detail/breastfeeding.Google Scholar
World Health Organization n.d. Accessed July 13, 2021. www.who.int/health-topics/breastfeeding.Google Scholar
World Health Organization 2015. International Statistical Classification of Diseases and Related Health Problems: 10th Revision (ICD-10). World Health Organization.Google Scholar
World Health Organization 2019. International statistical classification of diseases and related health problems (10th ed.). Retrieved from https://icd.who.int/browse10/2019/en#/F80-F89.Google Scholar
World Health Organization 2019. ICD-11: International Classification of Diseases (11th revision). https://icd.who.int.Google Scholar
World Health Organization 2020. ICD-11: International Classification of Diseases (11th Revision). https://icd.who.int/.Google Scholar
Wren, D. G., and Benson, J.. 2004. ‘Measuring Test Anxiety in Children: Scale Development and Internal Construct Validation’. Anxiety, Stress, and Coping 17 (3): 227–40.Google Scholar
Wu, S. S., Meyer, M. L., Maeda, U., et al. 2008. ‘Standardized Assessment of Strategy Use and Working Memory in Early Mental Arithmetic Performance’. Developmental Neuropsychology 33 (3): 365–93.Google Scholar
Wu, S. S., Chang, T. T., Majid, A., et al. 2009. ‘Functional Heterogeneity of Inferior Parietal Cortex during Mathematical Cognition Assessed with Cytoarchitectonic Probability Maps’. Cerebral Cortex 19 (12): 2930–45.Google Scholar
Wu, Y., Lu, Y.-C., Jacobs, M., et al. 2020. ‘Association of Prenatal Maternal Psychological Distress With Fetal Brain Growth, Metabolism, and Cortical Maturation’. JAMA Network Open 3 (1): e1919940.Google Scholar
Wynn, K. 1992a. ‘Addition and Subtraction by Human Infants’. Nature 358 (6389): 749–50.Google Scholar
Xia, Z., Hancock, R., and Hoeft, F.. 2017. ‘Neurobiological Bases of Reading Disorder Part I: Etiological Investigations’. Language and Linguistics Compass 11 (4): 1–18.Google Scholar
Xie, Y., Weng, J., Wang, C., et al. 2018. ‘The Impact of Long-Term Abacus Training on Modular Properties of Functional Brain Network’. NeuroImage 183 (December): 811–17.Google Scholar
Xu, F., and Spelke, E. S.. 2000. ‘Large Number Discrimination in 6-Month-Old Infants’. Cognition 74 (1): B1–11.Google Scholar
Yamada, Y., Stevens, C., Dow, M., et al. 2011. ‘Emergence of the Neural Network for Reading in Five-Year-Old Beginning Readers of Different Levels of Pre-Literacy Abilities: An fMRI Study’. NeuroImage 57 (3): 704–13.Google Scholar
Yamins, D. L. K., and DiCarlo, J. J. 2016. ‘Using Goal-Driven Deep Learning Models to Understand Sensory Cortex’. Nature Neuroscience 19 (3): 356–65.Google Scholar
Yang, J., McCandliss, B. D., Shu, H., and Zevin, J. D.. 2009. ‘Simulating Language-Specific and Language-General Effects in a Statistical Learning Model of Chinese Reading’. Journal of Memory and Language 61 (2): 238–57.Google Scholar
Yang, Y., Yang, Y. H., Li, J., Xu, M., and Bi., H.-Y. 2020. ‘An Audiovisual Integration Deficit Underlies Reading Failure in Nontransparent Writing Systems: An fMRI Study of Chinese Children with Dyslexia’. Journal of Neurolinguistics 54: 100884. https://doi.org/10.1016/j.jneuroling.2019.100884.Google Scholar
Yeatman, J. D., Dougherty, R. F., Ben-Shachar, M., and Wandell, B. A.. 2012. ‘Development of White Matter and Reading Skills’. Proceedings of the National Academy of Sciences of the United States of America 109 (44): E3045–53.Google Scholar
Yeatman, J. D., Dougherty, R. F., Rykhlevskaia, E., et al. 2011. ‘Anatomical Properties of the Arcuate Fasciculus Predict Phonological and Reading Skills in Children’. Journal of Cognitive Neuroscience 23 (11): 3304–17.Google Scholar
Yeatman, J. D., and White, A. L.. 2021. ‘Reading: The Confluence of Vision and Language’. Annual Review of Vision Science 7 (June): 487–517. https://doi.org/10.1146/annurev-vision-093019-113509.Google Scholar
Yeh, M. L., Gonda, Y., Mommersteeg, M. T. M., et al. 2014. ‘Robo1 Modulates Proliferation and Neurogenesis in the Developing Neocortex’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 34 (16): 5717–31.Google Scholar
Yeo, D.J., Wilkey, E. D., and Price, G. R.. 2017. ‘The Search for the Number Form Area: A Functional Neuroimaging Meta-Analysis’. Neuroscience and Biobehavioral Reviews 78 (July): 145–60.Google Scholar
Yin, R. 1980. Studying the Implementation of Public Programs. Boulder: Solar Energy Research Institute.Google Scholar
Yoncheva, Y. N., Blau, V. C., Maurer, U., and McCandliss, B. D.. 2010. ‘Attentional Focus during Learning Impacts N170 ERP Responses to an Artificial Script’. Developmental Neuropsychology 35 (4): 423–45.Google Scholar
Yoncheva, Y. N., Wise, J., and McCandliss, B.. 2015. ‘Hemispheric Specialization for Visual Words Is Shaped by Attention to Sublexical Units during Initial Learning’. Brain and Language 145–6 (June): 23–33.Google Scholar
Young, C. B., Wu, S. S., and Menon, V.. 2012. ‘The Neurodevelopmental Basis of Math Anxiety’. Psychological Science 23 (5): 492–501.Google Scholar
Yuan, Q., Rubic, M., Seah, J., et al. 2014. ‘Do Maternal Opioids Reduce Neonatal Regional Brain Volumes? A Pilot Study’. Journal of Perinatology: Official Journal of the California Perinatal Association 34 (12): 909–13.Google Scholar
Yuan, W., Holland, S. K., Cecil, K. M., et al. 2006. ‘The Impact of Early Childhood Lead Exposure on Brain Organization: A Functional Magnetic Resonance Imaging Study of Language Function’. Pediatrics 118 (3): 971–7.Google Scholar
Yu, X., Raney, T, Perdue, M. V., Zuk, J., et al. 2018. ‘Emergence of the Neural Network Underlying Phonological Processing from the Prereading to the Emergent Reading Stage: A Longitudinal Study’. Human Brain Mapping 39 (5): 2047–63.Google Scholar
Yu, X., Zuk, J, Perdue, M. V., et al. 2020. ‘Putative Protective Neural Mechanisms in Prereaders with a Family History of Dyslexia Who Subsequently Develop Typical Reading Skills’. Human Brain Mapping 41 (10): 2827–45.Google Scholar
Zacharopoulos, G., Sella, F., and Cohen Kadosh, R. 2021. ‘The Impact of a Lack of Mathematical Education on Brain Development and Future Attainment’. Proceedings of the National Academy of Sciences of the United States of America 118 (24). https://doi.org/10.1073/pnas.2013155118.Google Scholar
Zago, L., Petit, L., Mellet, E., et al. 2010. ‘Neural Correlates of Counting Large Numerosity’. ZDM: The International Journal on Mathematics Education 42 (6): 569–77.Google Scholar
Zagron, G., and Weinstock, M.. 2006. ‘Maternal Adrenal Hormone Secretion Mediates Behavioural Alterations Induced by Prenatal Stress in Male and Female Rats’. Behavioural Brain Research 175 (2): 323–8.Google Scholar
Zaigler, M., Rietbrock, S., Szymanski, J., et al. 2000. ‘Variation of CYP1A2-Dependent Caffeine Metabolism during Menstrual Cycle in Healthy Women’. International Journal of Clinical Pharmacology and Therapeutics 38 (5): 235–44.Google Scholar
Zamarian, L., Scherfler, C., Kremser, C., et al. 2018. ‘Arithmetic Learning in Advanced Age’. PloS One 13 (2): e0193529.Google Scholar
Zamarian, L., Ischebeck, A., and Delazer, M.. 2009. ‘Neuroscience of Learning Arithmetic: Evidence from Brain Imaging Studies’. Neuroscience and Biobehavioral Reviews 33 (6): 909–25.Google Scholar
Zatorre, R. J., Douglas Fields, R., and Johansen-berg, H.. 2012. ‘Plasticity in Gray and White: Neuroimaging Changes in Brain Structure during Learning’. Nature Publishing Group 15 (4): 528–36.Google Scholar
Zaunmüller, L., Domahs, F., Dressel, K., et al. 2009. ‘Rehabilitation of Arithmetic Fact Retrieval via Extensive Practice: A Combined fMRI and Behavioural Case-Study’. Neuropsychological Rehabilitation 19 (3): 422–43.Google Scholar
Zbornik, J. J., and Wallbrown, F. H.. 1991. ‘The Development and Validation of a Scale to Measure Reading Anxiety’. Chula Vista, Calif 28 (1): 2.Google Scholar
Zebian, S., and Ansari, D.. 2012. ‘Differences between Literates and Illiterates on Symbolic but Not Nonsymbolic Numerical Magnitude Processing’. Psychonomic Bulletin & Review 19: 93–100. https://doi.org/10.3758/s13423-011-0175-9.Google Scholar
Zeitlin, J., Saurel-Cubizolles, M. J., De Mouzon, J. et al. 2002. Fetal Sex and Preterm Birth: Are Males at Greater Risk? Hum Reprod. 17 (10): 2762–8.Google Scholar
Zhang, H., Yolton, K., Webster, G. M., et al. 2017. ‘Prenatal PBDE and PCB Exposures and Reading, Cognition, and Externalizing Behavior in Children’. Environmental Health Perspectives 125 (4): 746–52.Google Scholar
Zhang, J., Zhao, N., and Kong, Q. P.. 2019. ‘The Relationship between Math Anxiety and Math Performance: A Meta-Analytic Investigation’. Frontiers in Psychology 10 (August): 1613.Google Scholar
Zhang, T., Sidorchuk, A., Sevilla-Cermeño, L., et al. 2019. ‘Association of Cesarean Delivery With Risk of Neurodevelopmental and Psychiatric Disorders in the Offspring: A Systematic Review and Meta-Analysis’. JAMA Network Open 2 (8): e1910236.Google Scholar
Zhao, J., Liu, H., Li, J., et al. 2019. ‘Improving Sentence Reading Performance in Chinese Children with Developmental Dyslexia by Training Based on Visual Attention Span’. Scientific Reports 9 (1): 18964.Google Scholar
Zhao, J., Liu, M., Liu, H., and Huang, C.. 2018. ‘Increased Deficit of Visual Attention Span with Development in Chinese Children with Developmental Dyslexia’. Scientific Reports 8 (1): 3153.Google Scholar
Zhu, P. J., and Lovinger, D. M.. 2010. ‘Developmental Alteration of Endocannabinoid Retrograde Signaling in the Hippocampus’. Journal of Neurophysiology 103 (2): 1123–9.Google Scholar
Ziegler, J. C., Bertrand, D., Tóth, D., et al. 2010. ‘Orthographic Depth and Its Impact on Universal Predictors of Reading’. Psychological Science 21 (4): 551–9. https://doi.org/10.1177/0956797610363406.Google Scholar
Ziegler, J. C., Castel, C., Pech-Georgel, C., et al. 2008. ‘Developmental Dyslexia and the Dual Route Model of Reading: Simulating Individual Differences and Subtypes’. Cognition 107 (1): 151–78.Google Scholar
Ziegler, J. C., and Goswami, U.. 2005. ‘Reading Acquisition, Developmental Dyslexia, and Skilled Reading Across Languages: A Psycholinguistic Grain Size Theory’. Psychological Bulletin 131 (1): 3–29. https://doi.org/10.1037/0033-2909.131.1.3.Google Scholar
Ziegler, J. C., Perry, C., and Zorzi, M.. 2014. ‘Modelling Reading Development through Phonological Decoding and Self-Teaching: Implications for Dyslexia’. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 369 (1634): 20120397.Google Scholar
Ziegler, J. C., Perry, C., and Zorzi, M. 2020. ‘Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models’. Current Directions in Psychological Science 29 (3): 293–300.Google Scholar
Zirk-Sadowski, J., Lamptey, C., Devine, A., Haggard, M., and Szűcs, D.. 2014. ‘Young-Age Gender Differences in Mathematics Mediated by Independent Control or Uncontrollability’. Developmental Science 17 (3): 366–75.Google Scholar
Zoccolotti, P., De Luca, M., Marinelli, C. V., and Spinelli, Do. 2020. ‘Predicting Individual Differences in Reading, Spelling and Maths in a Sample of Typically Developing Children: A Study in the Perspective of Comorbidity’. PloS One 15 (4): e0231937.Google Scholar
Zoeller, R. T. 2005. ‘Environmental Chemicals as Thyroid Hormone Analogues: New Studies Indicate That Thyroid Hormone Receptors Are Targets of Industrial Chemicals?’ Molecular and Cellular Endocrinology 242 (1–2): 10–15.Google Scholar
Zorzi, M. 2010. ‘The Connectionist Dual Process (CDP) Approach to Modelling Reading Aloud’. The European Journal of Cognitive Psychology 22 (5): 836–60.Google Scholar
Zorzi, M., Barbiero, C., Facoetti, A., et al. 2012. ‘Extra-Large Letter Spacing Improves Reading in Dyslexia’. Proceedings of the National Academy of Sciences of the United States of America 109 (28): 11455–9.Google Scholar
Zorzi, M., Houghton, G., and Butterworth, B.. 1998a. ‘The Development of Spelling-Sound Relationships in a Model of Phonological Reading’. Language and Cognitive Processes 13 (2–3): 337–71.Google Scholar
Zorzi, M., Houghton, G., and Butterworth, B. 1998b. ‘Two Routes or One in Reading Aloud? A Connectionist Dual-Process Model’. Journal of Experimental Psychology. Human Perception and Performance 24 (4): 1131–61.Google Scholar
Zorzi, M., and Testolin, A.. 2018. ‘An Emergentist Perspective on the Origin of Number Sense’. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 373 (1740). https://doi.org/10.1098/rstb.2017.0043.Google Scholar
Zorzi, M., Testolin, A., and Stoianov, I. P.. 2013. ‘Modeling Language and Cognition with Deep Unsupervised Learning: A Tutorial Overview’. Frontiers in Psychology 4 (August): 515.Google Scholar
Zorzi, M., Stoianov, I., & Umiltà, C. 2005. ‘Computational Modeling of Numerical Cognition’. In J. I. D. Campbell (Ed.), Handbook of Mathematical Cognition (pp. 67–83). Psychology Press.Google Scholar
Zoubrinetzky, R., Collet, G., Nguyen-Morel, M.-A., Valdois, S., and Serniclaes, W.. 2019. ‘Remediation of Allophonic Perception and Visual Attention Span in Developmental Dyslexia: A Joint Assay’. Frontiers in Psychology 10 (July): 1502.Google Scholar
Zuijen, T. L. van, Plakas, A, Maassen, B. A. M., et al. 2013. ‘Infant ERPs Separate Children at Risk of Dyslexia Who Become Good Readers from Those Who Become Poor Readers’. Developmental Science 16 (4): 554–63.Google Scholar
Zuk, J., Bishop-Liebler, P., Ozernov-Palchik, O., et al. 2017. ‘Revisiting the “Enigma” of Musicians with Dyslexia: Auditory Sequencing and Speech Abilities’. Journal of Experimental Psychology. General 146 (4): 495–511.Google Scholar
Zuk, J., Dunstan, J., Norton, E., et al. 2021. ‘Multifactorial Pathways Facilitate Resilience among Kindergarteners at Risk for Dyslexia: A Longitudinal Behavioral and Neuroimaging Study’. Developmental Science 24 (1): e12983.Google Scholar

Secondary Sources

Aaron, P. G. 1997. ‘The Impending Demise of the Discrepancy Formula’. Review of Educational Research 67 (4): 461–502. https://doi.org/10.3102/00346543067004461.Google Scholar
Abbott, S. P., and Berninger, V. W.. 1999. ‘It’s Never Too Late to Remediate: Teaching Word Recognition to Students with Reading Disabilities in Grades 4–7’. Annals of Dyslexia 49: 223–50.Google Scholar
Abosi, O. 2007. ‘Educating Children with Learning Disabilities in Africa’. Learning Disabilities Research & Practice: A Publication of the Division for Learning Disabilities, Council for Exceptional Children 22 (3): 196–201.Google Scholar
Abramowicz, H. K., and Richardson, S. A.. 1975. ‘Epidemiology of Severe Mental Retardation in Children: Community Studies’. American Journal of Mental Deficiency 80 (1): 18–39.Google Scholar
Abreu, P. M. J. Engel de, M. Baldassi, M. L. Puglisi, and D. M. Befi-Lopes, . 2013. ‘Cross-Linguistic and Cross-Cultural Effects on Verbal Working Memory and Vocabulary: Testing Language-Minority Children with an Immigrant Background’. Journal of Speech, Language, and Hearing Research: JSLHR 56 (2): 630–42.Google Scholar
Adams, M. J., Foorman, B. R., Lundberg, I., and Beeler, T.. 1998. Phonemic Awareness in Young Children: A Classroom Curriculum. P.H. Brookes.Google Scholar
Agrawal, J., Barrio, B. L., Kressler, B., Hsiao, Y.-J., and Shankland, R. K.. 2019. ‘International Policies, Identification, and Services for Students with Learning Disabilities: An Exploration across 10 Countries’. Learning Disabilities: A Contemporary Journal 17 (1): 95–113.Google Scholar
Ainscow, M. 2016. ‘Collaboration as a Strategy for Promoting Equity in Education: Possibilities and Barriers’. Journal of Professional Capital and Community 1 (2). https://doi.org/10.1108/JPCC-12-2015-0013.Google Scholar
Akers, K. G., Martinez-Canabal, A., Restivo, L., et al. 2014. ‘Hippocampal Neurogenesis Regulates Forgetting during Adulthood and Infancy’. Science 344 (6184): 598–602.Google Scholar
Alberini, C. M., and Travaglia, A.. 2017. ‘Infantile Amnesia: A Critical Period of Learning to Learn and Remember’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 37 (24): 5783–95.Google Scholar
Alloway, T. P., Gathercole, S. E., Kirkwood, H., and Elliott, J.. 2009. ‘The Cognitive and Behavioral Characteristics of Children with Low Working Memory’. Child Development 80 (2): 606–21.Google Scholar
Alnahdi, G. 2015. ‘Teaching Reading for Students with Intellectual Disabilities: A Systematic Review’. International Education Studies 8 (9): 79.Google Scholar
Al Otaiba, S., Baker, K., Lan, P., et al. 2019. ‘Elementary Teacher’s Knowledge of Response to Intervention Implementation: A Preliminary Factor Analysis’. Annals of Dyslexia 69 (1): 34–53.Google Scholar
Altani, A., Protopapas, A., and Georgiou, G. K.. 2018. ‘Using Serial and Discrete Digit Naming to Unravel Word Reading Processes’. Frontiers in Psychology 9 (April): 524.Google Scholar
Altani, A., Protopapas, A., Katopodi, K., and Georgiou, G. K.. 2020. ‘From Individual Word Recognition to Word List and Text Reading Fluency’. Journal of Educational Psychology 112 (1): 22–35.Google Scholar
Amalric, M., and Dehaene, S.. 2017. ‘Cortical Circuits for Mathematical Knowledge: Evidence for a Major Subdivision within the Brain’s Semantic Networks’. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 373 (1740). https://doi.org/10.1098/rstb.2016.0515.Google Scholar
American Psychiatric Association. 2013. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). American Psychiatric Association Publishing.Google Scholar
American Psychiatric Association, and American Psychiatric Association: Task Force on Nomenclature and Statistics. 1980. Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association Publishing.Google Scholar
Anastasiou, D., Gardner, R., Michail, D., and et al. 2011. ‘Ethnicity and Exceptionality’. In J. Kauffman, M, Hallahan, D. P, and Cullen Pullen, P, Handbook of Special Education, 742–55. Routledge.Google Scholar
Andellini, M., Cannatà, V., Gazzellini, S., Bernardi, B., and Napolitano, A.. 2015. ‘Test-Retest Reliability of Graph Metrics of Resting State MRI Functional Brain Networks: A Review’. Journal of Neuroscience Methods 253 (September): 183–92.Google Scholar
Anderson, K. G. 1997. ‘Gender Bias and Special Education Referrals’. Annals of Dyslexia 47: 151–62. https://doi.org/10.1007/s11881-997-0024-8.Google Scholar
Anreiter, I., Sokolowski, H. M., and Sokolowski, M. B.. 2018. ‘Gene–environment Interplay and Individual Differences in Behavior’. Mind, Brain and Education: The Official Journal of the International Mind, Brain, and Education Society 12 (4): 200–11.Google Scholar
Anthony, J. L., and Lonigan, C. J.. 2004. ‘The Nature of Phonological Awareness: Converging Evidence From Four Studies of Preschool and Early Grade School Children’. Journal of Educational Psychology 96 (1): 43–55. https://doi.org/10.1037/0022-0663.96.1.43.Google Scholar
Anthony, J. L., Lonigan, C. J., Burgess, S. R., et al. 2002. ‘Structure of Preschool Phonological Sensitivity: Overlapping Sensitivity to Rhyme, Words, Syllables, and Phonemes’. Journal of Experimental Child Psychology 82 (1): 65–92.Google Scholar
Anthopolos, R., Kaufman, J. S., Messer, L. C., and Miranda, M. L.. 2014. ‘Racial Residential Segregation and Preterm Birth: Built Environment as a Mediator’. Epidemiology 25 (3): 397–405.Google Scholar
Araújo, S., and Faísca, L.. 2019. ‘A Meta-Analytic Review of Naming-Speed Deficits in Developmental Dyslexia’. Scientific Studies of Reading 23 (5). https://doi.org/10.1080/10888438.2019.1572758.Google Scholar
Araújo, S., Reis, Al, Petersson, K. M., and Faísca, L.. 2015. ‘Rapid Automatized Naming and Reading Performance: A Meta-Analysis’. Journal of Educational Psychology 107 (3): 868–83. https://doi.org/10.1037/edu0000006.Google Scholar
Arens, A. K., Marsh, H. W., Craven, R. G., et al. 2016. ‘Math Self-Concept in Preschool Children: Structure, Achievement Relations, and Generalizability across Gender’. Early Childhood Research Quarterly 36 (July): 391–403.Google Scholar
Arens, A. K., and Preckel, F.. 2018. ‘Testing the Internal/external Frame of Reference Model with Elementary School Children: Extension to Physical Ability and Intrinsic Value’. Contemporary Educational Psychology 54 (July): 199–211.Google Scholar
Arnold, A. P., Xu, J., Grisham, W., et al. 2004. ‘Minireview: Sex Chromosomes and Brain Sexual Differentiation’. Endocrinology 145 (3): 1057–62.Google Scholar
Artelt, C., Naumann, J., and Schneider, W.. 2010. ‘Lesemotivation Und Lernstrategien’. https://core.ac.uk/display/144486827.Google Scholar
Artiles, A. J. 1998. ‘The Dilemma of Difference: Enriching the Disproportionality Discourse with Theory and Context’. The Journal of Special Education 32 (1): 32–6.Google Scholar
Artiles, A. J. 2019. ‘Fourteenth Annual Brown Lecture in Education Research: Reenvisioning Equity Research: Disability Identification Disparities as a Case in Point’. Educational Researcher 48 (6): 325–35.Google Scholar
Arulmani, Gideon. 2004. Career Counselling: A Handbook. McGraw-Hill Education (India) Pvt Limited.Google Scholar
Asfaha, Y. M., Beckman, D., Kurvers, J., and Kroon, S.. 2009. ‘L2 Reading in Multilingual Eritrea: The Influences of L1 Reading and English Proficiency’. Journal of Research in Reading 32 (4): 351–65.Google Scholar
Aster, M.l G. von, and Shalev, R. S.. 2007. ‘Number Development and Developmental Dyscalculia’. Developmental Medicine and Child Neurology 49 (11): 868–73.Google Scholar
Atherton, O. E., Zheng, L. R., Bleidorn, W., and Robins, R. W.. 2019. ‘The Codevelopment of Effortful Control and School Behavioral Problems’. Journal of Personality and Social Psychology 117 (3): 659–73. https://doi.org/10.1037/pspp0000201.Google Scholar
Aunola, K., Leskinen, E., Lerkkanen, M.-K., and Nurmi, J.-E.. 2004. ‘Developmental Dynamics of Math Performance From Preschool to Grade 2’. Journal of Educational Psychology 96 (4): 699–713.Google Scholar
Baddeley, A. D., and Hitch, G.. 1974. ‘Working Memory’. In Psychology of Learning and Motivation, edited by Bower, Gordon H., 8:47–89. Academic Press.Google Scholar
Badian, N. A. 1986. ‘Nonverbal Disorders of Learning: The Reverse of Dyslexia?’ Annals of Dyslexia 36 (1): 253–69.Google Scholar
Badian, N. A. 1994. ‘Preschool Prediction: Orthographic and Phonological Skills, and Reading’. Annals of Dyslexia 44 (1): 1–25.Google Scholar
Badian, N. A. 1999. ‘Persistent Arithmetic, Reading, or Arithmetic and Reading Disability’. Annals of Dyslexia 49 (1): 43.Google Scholar
Bailey, D. 2019. ‘Chapter 13 – Explanations and Implications of Diminishing Intervention Impacts Across Time’. In Cognitive Foundations for Improving Mathematical Learning, edited by Geary, D. C., Berch, D. B., and Koepke, K. M., 5:321–46. Academic Press.Google Scholar
Bailey, D., Duncan, G. J., Odgers, C. L., and Yu., W. 2017. ‘Persistence and Fadeout in the Impacts of Child and Adolescent Interventions’. Journal of Research on Educational Effectiveness 10 (1): 7–39.Google Scholar
Bailey, D. H., Duncan, G. J., Cunha, F, Foorman, B. R., and Yeager, D. S.. 2020. ‘Persistence and Fade-Out of Educational-Intervention Effects: Mechanisms and Potential Solutions’. Psychological Science in the Public Interest: A Journal of the American Psychological Society 21 (2): 55–97.Google Scholar
Bailey, D. H., Duncan, G. J., Watts, T, Clements, D. H., and Sarama, J.. 2018. ‘Risky Business: Correlation and Causation in Longitudinal Studies of Skill Development’. The American Psychologist 73 (1): 81–94.Google Scholar
Bailey, D. H., Fuchs, L. S., Gilbert, J. K., Geary, D. C., and Fuchs, D.. 2020. ‘Prevention: Necessary but Insufficient? A 2-Year Follow-up of an Effective First-Grade Mathematics Intervention’. Child Development 91 (2): 382–400.Google Scholar
Bailey, D. H., Nguyen, T., Jenkins, J. M., et al. 2016. ‘Fadeout in an Early Mathematics Intervention: Constraining Content or Preexisting Differences?’ Developmental Psychology 52 (9): 1457–69.Google Scholar
Bailey, D. H., Watts, T. W., Littlefield, A. K., and Geary, D. C.. 2014. ‘State and Trait Effects on Individual Differences in Children’s Mathematical Development’. Psychological Science 25 (11): 2017–26.Google Scholar
Bailey, S. K., Aboud, K. S., Nguyen, T. Q., and Cutting, L. E.. 2018. ‘Applying a Network Framework to the Neurobiology of Reading and Dyslexia’. Journal of Neurodevelopmental Disorders 10 (1): 37.Google Scholar
Baker, L., and Wigfield, A.. 1999. ‘Dimensions of Children’s Motivation for Reading and Their Relations to Reading Activity and Reading Achievement’. Reading Research Quarterly 34 (4): 452–77.Google Scholar
Bal, A., Betters-Bubon, J., and Fish, R. E.. 2019. ‘A Multilevel Analysis of Statewide Disproportionality in Exclusionary Discipline and the Identification of Emotional Disturbance’. Education and Urban Society 51 (2): 247–68.Google Scholar
Balu, R., Zhu, P., Doolittle, F., et al. 2015. ‘Evaluation of Response to Intervention Practices for Elementary School Reading. NCEE 2016-4000’. National Center for Education Evaluation and Regional Assistance, November. http://files.eric.ed.gov/fulltext/ED560820.pdf.Google Scholar
Barahmand, Usha. 2008. ‘Arithmetic Disabilities: Training in Attention and Memory Enhances Arithmetic Ability’. Research Journal of Biological Sciences 3 (11): 1305–12.Google Scholar
Barbaresi, W. J., Katusic, S. K., Colligan, R. C., Weaver, A. L., and Jacobsen, S. J.. 2005. ‘Math Learning Disorder: Incidence in a Population-Based Birth Cohort, 1976–82, Rochester, Minn’. Ambulatory Pediatrics: The Official Journal of the Ambulatory Pediatric Association 5 (5): 281–9.Google Scholar
Barbiero, C., Montico, M., Lonciari, I., et al. 2019. ‘The Lost Children: The Underdiagnosis of Dyslexia in Italy. A Cross-Sectional National Study’. PloS One 14 (1): e0210448.Google Scholar
Barnett, W. S. 2011. ‘Effectiveness of Early Educational Intervention’. Science 333 (6045): 975–8.Google Scholar
Barnett, W. S., Jung, K, Yarosz, D. J., et al. 2008. ‘Educational Effects of the Tools of the Mind Curriculum: A Randomized Trial’. Early Childhood Research Quarterly 23 (3): 299–313.Google Scholar
Barrett, S., and Fudge, C.. 1981. Policy and Action: Essays on the Implementation of Public Policy. Methuen.Google Scholar
Barrouillet, P., and Fayol, M.. 1998. ‘From Algorithmic Computing to Direct Retrieval: Evidence from Number and Alphabetic Arithmetic in Children and Adults’. Memory & Cognition 26 (2): 355–68.Google Scholar
Barth, H. C., and Paladino, A. M.. 2011. ‘The Development of Numerical Estimation: Evidence against a Representational Shift’. Developmental Science 14 (1): 125–35.Google Scholar
Bastos, J. A., Cecato, A. M. T., Martins, M. R. I., Grecca, K. R. R., and Pierini, R.. 2016. ‘The Prevalence of Developmental Dyscalculia in Brazilian Public School System’. Arquivos de Neuro-Psiquiatria 74 (3): 201–6.Google Scholar
Battleday, R. M., Muller, T., Clayton, M. S., and Cohen Kadosh, R. 2014. ‘Mapping the Mechanisms of Transcranial Alternating Current Stimulation: A Pathway from Network Effects to Cognition’. Frontiers in Psychiatry / Frontiers Research Foundation 5 (November): 162.Google Scholar
Bauermeister, J. J., Shrout, P. E., Chávez, L., et al. 2007. ‘ADHD and Gender: Are Risks and Sequela of ADHD the Same for Boys and Girls?’ Journal of Child Psychology and Psychiatry, and Allied Disciplines 48 (8): 831–9.Google Scholar
Bauer, P. J. 2006. ‘Constructing a Past in Infancy: A Neuro-Developmental Account’. Trends in Cognitive Sciences 10 (4): 175–81.Google Scholar
Becker, J. R. 1981. ‘Differential Treatment of Females and Males in Mathematics Classes’. Journal for Research in Mathematics Education 12 (1): 40–53. https://doi.org/10.5951/jresematheduc.12.1.0040.Google Scholar
Bell, L. C., and Perfetti, C. A.. 1994. ‘Reading Skill: Some Adult Comparisons’. Journal of Educational Psychology 86 (2): 244–55. https://doi.org/10.1037/0022-0663.86.2.244.Google Scholar
Belsky, D. W., Moffitt, T. E., Corcoran, D. L., et al. 2016. ‘The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development’. Psychological Science 27 (7): 957–72.Google Scholar
Benavides-Varela, S., Callegher, C. Z., Fagiolini, B., Leo, I., Altoè, G., and Lucangeli, D. (2020). Effectiveness of digital-based interventions for children with mathematical learning difficulties: A meta-analysis. Computers & Education 157, 103953. https://doi.org/10.1016/j.compedu.2020.103953.Google Scholar
Ben-Yehudah, G., Hirshorn, E. A., Simcox, T, Perfetti, C. A., and Fiez, J. A.. 2019. ‘Chinese-English Bilinguals Transfer L1 Lexical Reading Procedures and Holistic Orthographic Coding to L2 English’. Journal of Neurolinguistics 50: 136–48. https://doi.org/10.1016/j.jneuroling.2018.01.002.Google Scholar
Berch, D. B., and Mazzocco, M. M. M.. 2007. Why Is Math So Hard for Some Children?: The Nature and Origins of Mathematical Learning Difficulties and Disabilities. Paul H. Brookes Publishing Company.Google Scholar
Bergen, E. van, de Jong, P. F., Maassen, B., and van der Leij, A.. 2014. ‘The Effect of Parents’ Literacy Skills and Children’s Preliteracy Skills on the Risk of Dyslexia’. Journal of Abnormal Child Psychology 42: 1187–200. https://doi.org/10.1007/s10802-014-9858-9.Google Scholar
Berkeley, S., Bender, W. N., Peaster, L. G., and Saunders, L.. 2009. ‘Implementation of Response to Intervention’. Journal of Learning Disabilities 42 (1): 85–95. https://doi.org/10.1177/0022219408326214.Google Scholar
Berkout, O. V., Young, J. N., and Gross, A. M.. 2011. ‘Mean Girls and Bad Boys: Recent Research on Gender Differences in Conduct Disorder’. Aggression and Violent Behavior 16 (6): 503–11.Google Scholar
Berman, P., and McLaughlin, M. W.. 1974. ‘Federal Programs Supporting Educational Change: Vol. I, A Model of Educational Change,’ January. www.rand.org/pubs/reports/R1589z1.html.Google Scholar
Berninger, V. W., Winn, W. D., Stock, P, et al. 2008. ‘Tier 3 Specialized Writing Instruction for Students with Dyslexia’. Reading and Writing 21 (1): 95–129.Google Scholar
Bhattacharya, A., and Ehri, L. C.. 2004. ‘Graphosyllabic Analysis Helps Adolescent Struggling Readers Read and Spell Words’. Journal of Learning Disabilities 37 (4): 331–48.Google Scholar
Bialystok, E., Luk, G, Peets, K. F., and Yang, S.. 2010. ‘Receptive Vocabulary Differences in Monolingual and Bilingual Children’. Bilingualism 13 (4): 525–31.Google Scholar
Bian, L., Leslie, S.-J., and Cimpian, A.. 2017. ‘Gender Stereotypes about Intellectual Ability Emerge Early and Influence Children’s Interests’. Science 355 (6323): 389–91. https://doi.org/10.1126/science.aah6524.Google Scholar
Bindman, S. W., Hindman, A. H., Bowles, R. P., and Morrison, F. J.. 2013. ‘The Contributions of Parental Management Language to Executive Function in Preschool Children’. Early Childhood Research Quarterly 28 (3): 529–39.Google Scholar
Bindman, S. W., Pomerantz, E. M., and Roisman, G. I.. 2015. ‘Do Children’s Executive Functions Account for Associations between Early Autonomy-Supportive Parenting and Achievement Through High School?’ Journal of Educational Psychology 107 (3): 756–70.Google Scholar
Birgisdottir, F., Gestsdottir, S., and Geldhof, G. J.. 2020. ‘Early Predictors of First and Fourth Grade Reading and Math: The Role of Self-Regulation and Early Literacy Skills’. Early Childhood Research Quarterly 53 (October): 507–19.Google Scholar
Bishop, D. V. M. 2010. ‘Which Neurodevelopmental Disorders Get Researched and Why?’ PloS One 5 (11): e15112.Google Scholar
Bishop, K. M., and Wahlsten, D.. 1997. ‘Sex Differences in the Human Corpus Callosum: Myth or Reality?’ Neuroscience & Biobehavioral Reviews. 21 (5): 581–601. https://doi.org/10.1016/s0149-7634(96)00049-8.Google Scholar
Bjorklund, D. F., and Causey, K. B.. 2017. Children’s Thinking: Cognitive Development and Individual Differences. SAGE Publications.Google Scholar
Bjorklund, D. F., and Pellegrini, A. D.. 2000. ‘Child Development and Evolutionary Psychology’. Child Development 71 (6): 1687–708.Google Scholar
Björn, P. M., Aro, M. T., Koponen, T. K., Fuchs, L. S., and Fuchs, D. H.. 2016. ‘The Many Faces of Special Education Within RTI Frameworks in the United States and Finland’. Learning Disability Quarterly 39 (1): 58–66. https://doi.org/10.1177/0731948715594787.Google Scholar
Blair, C., and Raver, C. C.. 2014. ‘Closing the Achievement Gap through Modification of Neurocognitive and Neuroendocrine Function: Results from a Cluster Randomized Controlled Trial of an Innovative Approach to the Education of Children in Kindergarten’. PloS One 9 (11): e112393.Google Scholar
Blair, C., and Razza, R. P.. 2007. ‘Relating Effortful Control, Executive Function, and False Belief Understanding to Emerging Math and Literacy Ability in Kindergarten’. Child Development 78 (2): 647–63.Google Scholar
Blanchett, W. J. 2010. ‘Telling It like It Is: The Role of Race, Class, & Culture in the Perpetuation of Learning Disability as a Privileged Category for the White Middle Class.’ Disability Studies Quarterly: DSQ 30 (2). https://doi.org/10.18061/dsq.v30i2.1233.Google Scholar
Bleeker, M. M., and Jacobs, J. E.. 2004. ‘Achievement in Math and Science: Do Mothers’ Beliefs Matter 12 Years Later?’ Journal of Educational Psychology 96 (1): 97–109. https://doi.org/10.1037/0022-0663.96.1.97.Google Scholar
Blevins-Knabe, B., and Musun-Miller, L.. 1996. ‘Number Use at Home by Children and Their Parents and Its Relationship to Early Mathematical Performance’. Early Development and Parenting: An International Journal of Research and Practice 5 (1): 35–45.Google Scholar
Blumenthal, Y., Voß, S., Sikora, S., and Hartke, B.. 2019. ‘Selected Findings of the First Large-Scale Implementation of Response to Intervention in Germany’. In Kollosche, D., Marcone, R., Knigge, M., Penteado, M., Skovsmose, O. (eds.) Inclusive Mathematics Education. Springer. https://doi.org/10.1007/978-3-030-11518-0_10.Google Scholar
Blum, W., and Schukajlow, S.. 2018. ‘Selbständiges Lernen Mit Modellierungsaufgaben – Untersuchung von Lernumgebungen Zum Modellieren Im Projekt DISUM’. In Evaluierte Lernumgebungen Zum Modellieren, edited by Schukajlow, S. and Blum, W., 51–72. Springer Fachmedien Wiesbaden.Google Scholar
Boada, R., and Pennington, B. F.. 2006. ‘Deficient Implicit Phonological Representations in Children with Dyslexia’. Journal of Experimental Child Psychology 95 (3): 153–93.Google Scholar
Boehner, J. A. 2002. No Child Left Behind Act of 2001. https://www.congress.gov/bill/107th-congress/house-bill/1.Google Scholar
Boer, M. van den, and de Jong, P. F.. 2015. ‘Parallel and Serial Reading Processes in Children’s Word and Nonword Reading’. Journal of Educational Psychology 107 (1): 141–51.Google Scholar
Bolger, D. J., Perfetti, C. A., and Schneider, W.. 2005. ‘Cross-Cultural Effect on the Brain Revisited: Universal Structures plus Writing System Variation’. Human Brain Mapping 25 (1): 92–104.Google Scholar
Booth, J. R., Burman, D. D., Meyer, J. R., et al. 2002. ‘Functional Anatomy of Intra- and Cross-Modal Lexical Tasks’. NeuroImage 16 (1): 7–22.Google Scholar
Booth, J. R., Burman, D. D., Meyer, J. R., et al. 2004. ‘Brain-Behavior Correlation in Children Depends on the Neurocognitive Network’. Human Brain Mapping 23: 99–108. https://doi.org/10.1002/hbm.20051.Google Scholar
Booth, J. R., Lu, D., Burman, D. D., et al. 2006. ‘Specialization of Phonological and Semantic Processing in Chinese Word Reading’. Brain Research 1071 (1): 197–207. https://doi.org/10.1016/j.brainres.2005.11.097.Google Scholar
Borckardt, J. J., Nahas, Z. H., Teal, J., et al. 2013. ‘The Painfulness of Active, but Not Sham, Transcranial Magnetic Stimulation Decreases Rapidly Over Time: Results From the Double-Blind Phase of the OPT-TMS Trial’. Brain Stimulation 6 (6): P925–8. https://doi.org/10.1016/j.brs.2013.04.009.Google Scholar
Borleffs, E., Maassen, B. A. M., Lyytinen, H., and Zwarts, F.. 2017. ‘Measuring Orthographic Transparency and Morphological-Syllabic Complexity in Alphabetic Orthographies: A Narrative Review’. Reading and Writing 30 (8): 1617–38.Google Scholar
Botswana, Republic of. 2015. ‘Education & Training Sector Strategic Plan (ETSSP 2015–2020)’. Government Printers Gaborone, Botswana.Google Scholar
Bower, C., Zimmermann, L., Verdine, B., et al. 2020. ‘Piecing Together the Role of a Spatial Assembly Intervention in Preschoolers’ Spatial and Mathematics Learning: Influences of Gesture, Spatial Language, and Socioeconomic Status’. Developmental Psychology 56 (4): 686–98.Google Scholar
Bowers, J. S. 2020. ‘Reconsidering the Evidence That Systematic Phonics Is More Effective Than Alternative Methods of Reading Instruction’. Educational Psychology Review 32 (3): 681–705.Google Scholar
Bowers, P. N., Kirby, J. R., and Hélène Deacon, S.. 2010. ‘The Effects of Morphological Instruction on Literacy Skills: A Systematic Review of the Literature’. Review of Educational Research 80 (2): 144–79.Google Scholar
Boyce, W. T., and Kobor, M. S.. 2015. ‘Development and the Epigenome: The “Synapse” of Gene-Environment Interplay’. Developmental Science 18 (1): 1–23.Google Scholar
Boyce, W. T., Obradovi, J., Bush, N. R., et al. 2012. ‘Social Stratification, Classroom Climate, and the Behavioral Adaptation of Kindergarten Children’. Proceedings of the National Academy of Sciences 109 (6178): 17168–73. https://doi.org/10.1073/pnas.1201730109.Google Scholar
Boyes, M. E., Leitão, S., Claessen, M., et al. 2020. ‘Piloting “Clever Kids”: A Randomized-Controlled Trial Assessing Feasibility, Efficacy, and Acceptability of a Socioemotional Well-Being Programme for Children with Dyslexia’. The British Journal of Educational Psychology, December, e12401.Google Scholar
Bradley, L., and Bryant, P. E.. 1983. ‘Categorizing Sounds and Learning to Read – a Causal Connection’. Nature 301: 419–21. https://doi.org/10.1038/301419a0.Google Scholar
Brady, S. A., and Shankweiler, D. P.. 2013. Phonological Processes in Literacy: A Tribute to Isabelle Y. Liberman. Routledge.Google Scholar
Breznitz, Z., Rubinsten, O, Molfese, V. J., and Molfese, D. L., eds. 2012. Reading, Writing, Mathematics and the Developing Brain: Listening to Many Voices. 2012 ed. Literacy Studies 6. Springer.Google Scholar
Brighina, F., Raieli, V., Messina, L. M., et al. 2019. ‘Non-Invasive Brain Stimulation in Pediatric Migraine: A Perspective From Evidence in Adult Migraine’. Frontiers in Neurology 10. https://doi.org/10.3389/fneur.2019.00364.Google Scholar
Brinkman, W. B., Sherman, S. N., Zmitrovich, A. R., et al. 2009. ‘Parental Angst Making and Revisiting Decisions about Treatment of Attention-Deficit/Hyperactivity Disorder’. Pediatrics 124 (2): 580–9.Google Scholar
Brown, M. C., Sibley, D. E., Washington, J. A., et al. 2015. ‘Impact of Dialect Use on a Basic Component of Learning to Read’. Frontiers in Psychology 6 (March): 196.Google Scholar
Bruce, S. M., and Venkatesh, K.. 2014. ‘Special Education Disproportionality in the United States, Germany, Kenya, and India’. Disability & Society 29 (6): 908–21.Google Scholar
Brunoni, A. R., Sampaio-Junior, B., Moffa, A. H., et al. 2019. ‘Noninvasive Brain Stimulation in Psychiatric Disorders: A Primer’. Revista Brasileira de Psiquiatria (Sao Paulo, Brazil: 1999) 41 (1): 70–81.Google Scholar
Brunoni, A. Ru., and Vanderhasselt, M.-A.. 2014. ‘Working Memory Improvement with Non-Invasive Brain Stimulation of the Dorsolateral Prefrontal Cortex: A Systematic Review and Meta-Analysis’. Brain and Cognition 86 (April): 1–9.Google Scholar
Bryant, B. R., Bryant, D. Pe., Porterfield, J., et al. 2016. ‘The Effects of a Tier 3 Intervention on the Mathematics Performance of Second Grade Students With Severe Mathematics Difficulties’. Journal of Learning Disabilities 49 (2): 176–88.Google Scholar
Bryant, D. P., Bryant, B. R., Roberts, G., et al. 2011. ‘Early Numeracy Intervention Program for First-Grade Students with Mathematics Difficulties’. Exceptional Children 78 (1): 7–23.Google Scholar
Bryant, P. 2002. ‘It Doesn’t Matter Whether Onset and Rime Predicts Reading Better Than Phoneme Awareness Does or Vice Versa’. Journal of Experimental Child Psychology 82 (1): 41–6. https://doi.org/10.1006/jecp.2002.2672.Google Scholar
Bub, D. N., Arguin, M., and Lecours, A. R.. 1993. ‘Jules Dejerine and His Interpretation of Pure Alexia’. Brain and Language 45 (4): 531–59.Google Scholar
Buchweitz, A., Shinkareva, S. V., Mason, R. A., Mitchell, T. M., and Just, M. A.. 2012. ‘Identifying Bilingual Semantic Neural Representations across Languages’. Brain and Language 120 (3): 282–9. https://doi.org/10.1016/j.bandl.2011.09.003.Google Scholar
Buckingham, J., Beaman, R., and Wheldall, K.. 2014. ‘Why Poor Children Are More Likely to Become Poor Readers: The Early Years’. Educational Review 66 (4): 428–46. https://doi.org/10.1080/00131911.2013.795129.Google Scholar
Bueren, N. E. R. van, Reed, T. L., Nguyen, V., et al. 2021. ‘Personalized Closed-Loop Brain Stimulation for Effective Neurointervention Across Participants’. PLOS Computational Biology 17(9): e1008886. https://doi.org/10.1101/2021.03.18.436018.Google Scholar
Bulajić, A., Despotović, M., and Lachmann, T.. 2019. ‘Understanding Functional Illiteracy from a Policy, Adult Education, and Cognition Point of View: Towards a Joint Referent Framework’. Zeitschrift Für Neuropsychologie 30 (2): 109–22. https://doi.org/10.1024/1016-264x/a000255.Google Scholar
Bull, R., and Scerif, G.. 2001. ‘Executive Functioning as a Predictor of Children’s Mathematics Ability: Inhibition, Switching, and Working Memory’. Developmental Neuropsychology 19 (3): 273–93.Google Scholar
Bulthé, J., Prinsen, J., Vanderauwera, J., et al. 2019a. ‘Multi-Method Brain Imaging Reveals Impaired Representations of Number as Well as Altered Connectivity in Adults with Dyscalculia’. NeuroImage 190: 289–302. https://doi.org/10.1016/j.neuroimage.2018.06.012.Google Scholar
Bulthé, J., Prinsen, J., Vanderauwera, J. 2019b. ‘Multi-Method Brain Imaging Reveals Impaired Representations of Number as Well as Altered Connectivity in Adults with Dyscalculia’. NeuroImage 190 (April): 289–302.Google Scholar
Bunea, I. M., Szentágotai-Tătar, A., and Miu, A. C.. 2017. ‘Early-Life Adversity and Cortisol Response to Social Stress: A Meta-Analysis’. Translational Psychiatry 7 (12): 1–8.Google Scholar
Burgess, A. P., Witton, C., Shapiro, L., and Talcott, J. B.. 2018. ‘From Subtypes to Taxons: Identifying Distinctive Profiles of Reading Development in Children’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 213–33. Springer International Publishing.Google Scholar
Bus, A. G., and van IJzendoorn, M. H.. 1999. ‘Phonological Awareness and Early Reading: A Meta-Analysis of Experimental Training Studies’. Journal of Educational Psychology 91 (3): 403–14. https://doi.org/10.1037/0022-0663.91.3.403.Google Scholar
Busch, J., Schmidt, C., and Grube, D.. 2015. ‘Arithmetic Fact Retrieval’. Zeitschrift Für Psychologie 223 (2): 110–19.Google Scholar
Buschmann, A., Jooss, B., Rupp, A., et al. 2009. ‘Parent Based Language Intervention for 2-Year-Old Children with Specific Expressive Language Delay: A Randomised Controlled Trial’. Archives of Disease in Childhood 94 (2): 110–16.Google Scholar
Butterworth, B., and Kovas, Y.. 2013. ‘Understanding Neurocognitive Developmental Disorders Can Improve Education for All’. Science 340 (6130): 300–5.Google Scholar
Calcus, A., Hoonhorst, I., Colin, C., Deltenre, P., and Kolinsky, R.. 2018. ‘The ‘Rowdy Classroom Problem’ in Children with Dyslexia: A Review’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 183–211. Springer International Publishing.Google Scholar
Calhoon, M. B., Greenberg, D., and Vincent Hunter, C.. 2010. ‘A Comparison of Standardized Spelling Assessments: Do They Measure Similar Orthographic Qualities?’ Learning Disability Quarterly: Journal of the Division for Children with Learning Disabilities 33 (3): 159–70.Google Scholar
Camilli, G., Vargas, S., Ryan, S., and Barnett, W. S.. 2010. ‘Meta-Analysis of the Effects of Early Education Interventions on Cognitive and Social Development’. Teachers College Record 112 (3): 579–620.Google Scholar
Campbell, F. A., and Ramey, C. T.. 1994. ‘Effects of Early Intervention on Intellectual and Academic Achievement: A Follow-up Study of Children from Low-Income Families’. Child Development 65 (2): 684–98.Google Scholar
Campbell, F. A., Ramey, C. T., Pungello, E., Sparling, J., and Miller-Johnson, S.. 2002. ‘Early Childhood Education: Young Adult Outcomes From the Abecedarian Project’. Applied Developmental Science 6 (1): 42–57.Google Scholar
Campbell, F., Conti, G., Heckman, J. J., et al 2014. ‘Early Childhood Investments Substantially Boost Adult Health’. Science 343 (6178): 1478–85.Google Scholar
Cantlon, J. F. 2012. ‘Math, Monkeys, and the Developing Brain’. Proceedings of the National Academy of Sciences of the United States of America 109 Suppl 1 (June): 10725–32.Google Scholar
Cao, F., Vu, M., Chan, D. H. L., et al. 2013. ‘Writing Affects the Brain Network of Reading in Chinese: A Functional Magnetic Resonance Imaging Study’. Human Brain Mapping 34: 1670–84. https://doi.org/10.1002/hbm.22017.Google Scholar
Cao, F., Yan, X., Wang, Z., et al. 2017. ‘Neural Signatures of Phonological Deficits in Chinese Developmental Dyslexia’. NeuroImage 146 (February): 301–11.Google Scholar
Caplan, G. 1964. ‘Principles of Preventive Psychiatry’ 304. https://psycnet.apa.org/fulltext/1965-02239-000.pdf.Google Scholar
Caplan, G 1974. Support Systems and Community Mental Health: Lectures on Concept Development. Behavioral Publications.Google Scholar
Cappelletti, M., and Price, C. J.. 2014. ‘Residual Number Processing in Dyscalculia’. NeuroImage. Clinical 4: 18–28.Google Scholar
Caravolas, M. 2004. ‘Spelling Development in Alphabetic Writing Systems: A Cross-Linguistic Perspective’. European Psychologist 9 (1): 3–14.Google Scholar
Caravolas, M., Hulme, C., and Snowling, M. J.. 2001. ‘The Foundations of Spelling Ability: Evidence from a 3-Year Longitudinal Study’. Journal of Memory and Language 45 (4): 751–74. https://doi.org/10.1006/jmla.2000.2785.Google Scholar
Caravolas, M., Lervåg, A., Defior, S., Málková, G. S., and Hulme, C.. 2013. ‘Different Patterns, but Equivalent Predictors, of Growth in Reading in Consistent and Inconsistent Orthographies’. Psychological Science 24 (8): 1398–1407.Google Scholar
Caravolas, M., Lervåg, A., Mousikou, P., et al. 2012. ‘Common Patterns of Prediction of Literacy Development in Different Alphabetic Orthographies’. Psychological Science 23 (6): 678–86.Google Scholar
Carey, S., and Barner, D.. 2019. ‘Ontogenetic Origins of Human Integer Representations’. Trends in Cognitive Sciences 23 (10): 823–35.Google Scholar
Carlisle, J. F. 2003. ‘Morphology Matters in Learning to Read: A Commentary’. Reading Psychology 24 (3–4): 291–322.Google Scholar
Carreiras, M., Duñabeitia, J. A., and Perea, M.. 2007. ‘Reading Words, NUMB3R5 and YMßOL’. Trends in Cognitive Sciences 11 (11): 454–5.Google Scholar
Carrol, J. M., Snowling, M. J., Stevenson, J., and Hulme, C.. 2003. ‘The Development of Phonological Awareness in Preschool Children’. Developmental Psychology 39 (5): 913.Google Scholar
Carroll, J. M., Maughan, B., Goodman, R., and Meltzer, H.. 2005. ‘Literacy Difficulties and Psychiatric Disorders: Evidence for Comorbidity’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 46 (5): 524–32.Google Scholar
Casey, B. M., Lombardi, C. M., Thomson, D., et al. 2018. ‘Maternal Support of Children’s Early Numerical Concept Learning Predicts Preschool and First-Grade Math Achievement’. Child Development 89 (1): 156–73.Google Scholar
Casey, B. M., Nuttall, R. L., and Pezaris, E.. 1997. ‘Mediators of Gender Differences in Mathematics College Entrance Test Scores: A Comparison of Spatial Skills with Internalized Beliefs and Anxieties’. Developmental Psychology 33 (4): 669–80. https://doi.org/10.1037/0012-1649.33.4.669.Google Scholar
Castle, M. N. 2004. Individuals with Disabilities Education Improvement Act of 2004. www.congress.gov/bill/108th-congress/house-bill/1350.Google Scholar
Castles, A., and Coltheart, M.. 2004. ‘Is There a Causal Link from Phonological Awareness to Success in Learning to Read?’ Cognition 91 (1): 77–111.Google Scholar
Castles, A., Rastle, K., and Nation, K.. 2018. ‘Ending the Reading Wars: Reading Acquisition from Novice to Expert’. Psychological Science in the Public Interest, 19 (1), 5–51. https://doi.org/10.1177/1529100618772271.Google Scholar
Castro, M. V. de, Bissaco, M. A. S., Panccioni, B. M., Rodrigues, S. C.M., and Domingues, A. M.. 2014. ‘Effect of a Virtual Environment on the Development of Mathematical Skills in Children with Dyscalculia’. PloS One 9 (7): e103354.Google Scholar
Cattaneo, Z., Pisoni, A., and Papagno, C.. 2011. ‘Transcranial Direct Current Stimulation over Broca’s Region Improves Phonemic and Semantic Fluency in Healthy Individuals’. Neuroscience 183: 64–70. https://doi.org/10.1016/j.neuroscience.2011.03.058.Google Scholar
Catts, H. W., McIlraith, A., Sittner Bridges, M, and Corcoran Nielsen, D. 2017. ‘Viewing a Phonological Deficit within a Multifactorial Model of Dyslexia’. Reading and Writing 30 (3): 613–29.Google Scholar
Catts, H. W. 1993. ‘The Relationship between Speech-Language Impairments and Reading Disabilities’. Journal of Speech and Hearing Research 36 (5): 948–58.Google Scholar
Ceci, S. J., Ginther, D. K., Kahn, S., and Williams, W. M.. 2014. ‘Women in Academic Science: A Changing Landscape’. Psychological Science in the Public Interest: A Journal of the American Psychological Society 15 (3): 75–141.Google Scholar
Chan, D. W., Ho, C. S.‐H., Tsang, S.‐M., Lee, S.‐H., and Chung, K.K. H.. 2007. ‘Prevalence, Gender Ratio and Gender Differences in Reading‐related Cognitive Abilities among Chinese Children with Dyslexia in Hong Kong’. Educational Studies 33 (2): 249–65.Google Scholar
Changizi, M. A., Zhang, Q., Ye, H., and Shimojo, S.. 2006. ‘The Structures of Letters and Symbols throughout Human History Are Selected to Match Those Found in Objects in Natural Scenes’. The American Naturalist 167 (5): E117–39.Google Scholar
Chan, W. Lan, W., Au, T. K., and Tang, J.. 2013. ‘Developmental Dyscalculia and Low Numeracy in Chinese Children’. Research in Developmental Disabilities 34 (5): 1613–22.Google Scholar
Chaplin, T. M., and Aldao, A.. 2013. ‘Gender Differences in Emotion Expression in Children: A Meta-Analytic Review’. Psychological Bulletin 139 (4): 735–65. https://doi.org/10.1037/a0030737.Google Scholar
Chapman, J. W., Tunmer, W. E., and Allen, R.. 2003. ‘Findings from the International Adult Literacy Survey on the Incidence and Correlates of Learning Disabilities in New Zealand: Is Something Rotten in the State of New Zealand?’ Dyslexia 9 (2): 75–98.Google Scholar
Cheam, F., and Jocelyn, C. W. L.. 2009. ‘Early Intervention for Pupils At-Risk of Mathematics Difficulties’. In Mathematics Education, 2: 370–86.Series on Mathematics Education. WORLD SCIENTIFIC.Google Scholar
Chenault, B., Thomson, J., Abbott, R. D., and Berninger, V. W.. 2006. ‘Effects of Prior Attention Training on Child Dyslexics’ Response to Composition Instruction’. Developmental Neuropsychology 29 (1): 243–60.Google Scholar
Cheng, D., Xiao, Q., Cui, J., et al. 2020. ‘Short-Term Numerosity Training Promotes Symbolic Arithmetic in Children with Developmental Dyscalculia: The Mediating Role of Visual Form Perception’. Developmental Science 23 (4): e12910.Google Scholar
Cheng, D., Xiao, Q., Cui, J., Chen, C., and Zeng, J.. 2020. ‘Short‐term Numerosity Training Promotes Symbolic Arithmetic in Children with Developmental Dyscalculia: The Mediating Role of Visual Form Perception’. Developmental Science 23 (4): e12910. https://onlinelibrary.wiley.com/doi/abs/10.1111/desc.12910?casa_token=gcwtUsLsolkAAAAA:VABRViSQSsNpY2Gnhl69jhw9OlN-efxC74Qatk2yVCOJFFqIFypUzECm5l5rDr8k8eIMWpcc6yLSEFA.Google Scholar
Chen, H.-Yu, Chang, E. C., Chen, S. H. Y., Lin, Y.-C., and Wu, D. H.. 2016. ‘Functional and Anatomical Dissociation between the Orthographic Lexicon and the Orthographic Buffer Revealed in Reading and Writing Chinese Characters by fMRI’. NeuroImage 129 (1): 105–16. https://doi.org/10.1016/j.neuroimage.2016.01.009.Google Scholar
Chen, H., Gu, X.-H., Zhou, Y., et al. 2017. ‘A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability’. Scientific Reports 7 (1): 1–9.Google Scholar
Chen, Q., and Li., J. 2014. ‘Association between Individual Differences in Non-Symbolic Number Acuity and Math Performance: A Meta-Analysis’. Acta Psychologica 148 (May): 163–72.Google Scholar
Cheung, C.-N., Sung, J. Y., and Lourenco, S. F.. 2020. ‘Does Training Mental Rotation Transfer to Gains in Mathematical Competence? Assessment of an at-Home Visuospatial Intervention’. Psychological Research 84 (7): 2000–17.Google Scholar
Cheung, H., Chen, H.-C., Lai, C. Y., Wong, O. C., and Hills, M.. 2001. ‘The Development of Phonological Awareness: Effects of Spoken Language Experience and Orthography’. Cognition 81 (3): 227–41. https://doi.org/10.1016/s0010-0277(01)00136-6.Google Scholar
Chia, N. K. H. n.d. ‘An Investigative Study on the Learning Difficulties in Mathematics Encountered by Primary 4 Children: In Search of a Cognitive Equation for Mathematics Learning’. Accessed April 15, 2021. http://aasep.org/fileadmin/user_upload/Protected_Directory/JAASEP/2011_Winter/Investigative_Study_on_Learning_Difficulties_in_Mathematics_Encountered_by_Primary_4_Children-In_Search_of_Cognitive_Equation_for_Mathematics_Learning.pdf.Google Scholar
Chia, N. K. H., Ng, A. G. T., Tan, S. S. K., and Wee, L. H.. 2014. ‘A Comparison of Cognitive Equations of Mathematics Learning Process between the American and Singaporean Students with Dyscalculia’. Educational Research International 1 (3): 1–14.Google Scholar
Chodura, S., Kuhn, J.-T., and Holling, H.. 2015. ‘Interventions for Children With Mathematical Difficulties’. Zeitschrift Für Psychologie 223 (2): 129–44.Google Scholar
Chou, T.-L., Davis, M. H., Marslen-Wilson, W. D., and Booth, J. R.. 2006. ‘Phonological Priming in Visual Word Recognition for English Words: An Event-Related Functional MRI Study’. Chinese Journal of Psychology 48 (4): 329–46.Google Scholar
Chu, F. W., vanMarle, K., and Geary, D. C.. 2015. ‘Early Numerical Foundations of Young Children’s Mathematical Development’. Journal of Experimental Child Psychology 132 (April): 205–12.Google Scholar
Cipora, K., Patro, K., and Nuerk, H.-C.. 2015. ‘Are Spatial-Numerical Associations a Cornerstone for Arithmetic Learning? The Lack of Genuine Correlations Suggests No’. Mind, Brain and Education: The Official Journal of the International Mind, Brain, and Education Society 9 (4): 190–206.Google Scholar
Cirillo, G., Di Pino, G., Capone, F., et al. 2017. ‘Neurobiological after-Effects of Non-Invasive Brain Stimulation’. Brain Stimulation 10 (1): 1–18.Google Scholar
Claessens, A., Duncan, G., and Engel, M.. 2009. ‘Kindergarten Skills and Fifth-Grade Achievement: Evidence from the ECLS-K’. Economics of Education Review 28 (4): 415–27. https://doi.org/10.1016/j.econedurev.2008.09.003.Google Scholar
Clark, C. A. C., Sheffield, T. D., Wiebe, S. A., and Espy, K. A.. 2013. ‘Longitudinal Associations between Executive Control and Developing Mathematical Competence in Preschool Boys and Girls’. Child Development 84 (2): 662–77.Google Scholar
Clayton, S., and Gilmore, C.. 2015. ‘Inhibition in Dot Comparison Tasks’. ZDM: The International Journal on Mathematics Education 47 (5): 759–70.Google Scholar
Clements, A. M., Rimrodt, S. L., Abel, J. R., et al. 2006. ‘Sex Differences in Cerebral Laterality of Language and Visuospatial Processing’. Brain and Language 98 (2): 150–8.Google Scholar
Clements, D. H., and Sarama, J.. 2007. ‘Effects of a Preschool Mathematics Curriculum: Summative Research on the Building Blocks Project’. Journal for Research in Mathematics Education 38 (2): 136–63.Google Scholar
Clements, D. H., Sarama, J, Wolfe, C. B., and Spitler, M. E.. 2013. ‘Longitudinal Evaluation of a Scale-Up Model for Teaching Mathematics With Trajectories and Technologies: Persistence of Effects in the Third Year’. American Educational Research Journal 50 (4): 812–50.Google Scholar
Coard, B. 1971. ‘How the West Indian Child Is Made Educationally Subnormal in the British School System: The Scandal of the Black Child in Schools in Britain’. ERIC. https://eric.ed.gov/?id=ED054281.Google Scholar
Coburn, C. E. 2003. ‘Rethinking Scale: Moving Beyond Numbers to Deep and Lasting Change’. Educational Researcher 32 (6): 3–12. https://doi.org/10.3102/0013189x032006003.Google Scholar
Cohen Kadosh, R., Cohen Kadosh, K, Schuhmann, T., et al. 2007. ‘Virtual Dyscalculia Induced by Parietal-Lobe TMS Impairs Automatic Magnitude Processing’. Current Biology: CB 17 (8): 689–93.Google Scholar
Cohen Kadosh, R., Dowker, A., Heine, A., Kaufmann, L., and Kucian, K.. 2013. ‘Interventions for Improving Numerical Abilities: Present and Future’. Trends in Neuroscience and Education 2 (2): 85–93.Google Scholar
Cohen Kadosh, R., Levy, N., O’Shea, J., Shea, N., and Savulescu, J.. 2012. ‘The Neuroethics of Non-Invasive Brain Stimulation’. Current Biology: CB 22 (4): R108–11.Google ScholarPubMed
Cohen Kadosh, R., Soskic, S, Iuculano, T., Kanai, R., and Walsh, V.. 2010. ‘Modulating Neuronal Activity Produces Specific and Long-Lasting Changes in Numerical Competence’. Current Biology: CB 20 (22): 2016–20.Google Scholar
Colé, P., Duncan, L. G., and Blaye, A.. 2014. ‘Cognitive Flexibility Predicts Early Reading Skills’. Frontiers in Psychology 5 (June): 565.Google Scholar
Coltheart, M. 1996. ‘Phonological Dyslexia: Past and Future Issues’. Cognitive Neuropsychology 13 (6): 749–62.Google Scholar
Coltheart, M. 2014. ‘The Neuronal Recycling Hypothesis for Reading and the Question of Reading Universals’. Mind & Language 29 (3): 255–69.Google Scholar
Conn, K. M. 2017. ‘Identifying Effective Education Interventions in Sub-Saharan Africa: A Meta-Analysis of Impact Evaluations’. Review of Educational Research 87 (5): 863–98.Google Scholar
Connor, D. J., and Ferri, B. A.. 2010. ‘Introduction to DSQ Special Issue: ‘Why Is There Learning Disabilities?’ – Revisiting Christine Sleeter’s Socio-Political Construction of Disability Two Decades on’. Disability Studies Quarterly: DSQ 30 (2). https://doi.org/10.18061/dsq.v30i2.1229.Google Scholar
Cooperstock, M., and Campbell, J.. 1996. ‘Excess Males in Preterm Birth: Interactions with Gestational Age, Race, and Multiple Birth’. Obstetrics & Gynecology 88 (2): 189–93. https://doi.org/10.1016/0029-7844(96)00106-8.Google Scholar
Cormier, E. 2012. ‘How Parents Make Decisions to Use Medication to Treat Their Child’s ADHD: A Grounded Theory Study’. Journal of the American Psychiatric Nurses Association 18 (6): 345–56.Google Scholar
Cornu, V., Hornung, C., Schiltz, C., and Martin, R.. 2017. ‘How Do Different Aspects of Spatial Skills Relate to Early Arithmetic and Number Line Estimation?’ Journal of Numerical Cognition 3 (2): 309–43.Google Scholar
Coslett, H. B., and Monsul, N.. 1994. ‘Reading with the Right-Hemisphere: Evidence from Transcranial Magnetic Stimulation’. Brain and Language 46 (2): 198–211. https://doi.org/10.1006/brln.1994.1012.Google Scholar
Costanzo, F., Menghini, D., Caltagirone, C., Oliveri, M., and Vicari, S.. 2013. ‘How to Improve Reading Skills in Dyslexics: The Effect of High Frequency rTMS’. Neuropsychologia 51 (14): 2953–59.Google Scholar
Costanzo, F., Rossi, S., Varuzza, C., et al. 2019. ‘Long-Lasting Improvement Following tDCS Treatment Combined with a Training for Reading in Children and Adolescents with Dyslexia’. Neuropsychologia 130 (July): 38–43.Google Scholar
Costanzo, F., Varuzza, C., Rossi, S., et al. 2016a. ‘Evidence for Reading Improvement Following tDCS Treatment in Children and Adolescents with Dyslexia’. Restorative Neurology and Neuroscience 34 (2): 215–26.CrossRefGoogle ScholarPubMed
Costanzo, F., Varuzza, C., Rossi, S., et al. 2016b. ‘Reading Changes in Children and Adolescents with Dyslexia after Transcranial Direct Current Stimulation’. Neuroreport 27 (5): 295–300.Google Scholar
Costenbader, V., and Markson, S.. 1998. ‘School Suspension: A Study with Secondary School Students’. Journal of School Psychology 36 (1): 59–82.CrossRefGoogle Scholar
Cotton, S. M., Crewther, D. P., and Crewther, S. G.. 2005. ‘Measurement Error: Implications for Diagnosis and Discrepancy Models of Developmental Dyslexia’. Dyslexia 11 (3): 186–202.Google Scholar
Coupé, C., Oh, Y., Dediu, D., and Pellegrino, F.. 2019. ‘Different Languages, Similar Encoding Efficiency: Comparable Information Rates across the Human Communicative Niche’. Science Advances 5 (9). https://doi.org/10.1126/sciadv.aaw2594.Google Scholar
Cui, J., Zhang, Y., Wan, S., Chen, C., Zeng, J., and Zhou, X.. 2019. ‘Visual Form Perception Is Fundamental for Both Reading Comprehension and Arithmetic Computation’. Cognition 189 (August): 141–54.Google Scholar
Cunningham, A. J., Burgess, A. P., Witton, C, Talcott, J. B., and Shapiro, L. R.. 2021. ‘Dynamic Relationships between Phonological Memory and Reading: A Five Year Longitudinal Study from Age 4 to 9’. Developmental Science 24 (1): e12986. https://doi.org/10.1111/desc.12986.Google Scholar
Cvencek, D., Meltzoff, A. N., and Greenwald, A. G.. 2011. ‘Math-Gender Stereotypes in Elementary School Children’. Child Development 83 (3): 766–79. https://doi.org/10.1111/j.1467-8624.2010.01529.x.Google Scholar
Dackermann, T., Fischer, U., Nuerk, H.-C., Cress, U., and Moeller, K.. 2017. ‘Applying Embodied Cognition: From Useful Interventions and Their Theoretical Underpinnings to Practical Applications’. ZDM: The International Journal on Mathematics Education 49 (4): 545–57.Google Scholar
Dackermann, T., Huber, S., Bahnmueller, J., Nuerk, H.-C., and Moeller, K.. 2015. ‘An Integration of Competing Accounts on Children’s Number Line Estimation’. Frontiers in Psychology 6. https://doi.org/10.3389/fpsyg.2015.00884.Google Scholar
Da, J. 2004. ‘A Corpus-Based Study of Character and Bigram Frequencies in Chinese E-Texts and Its Implications for Chinese Language Instruction’. In Proceedings of the Fourth International Conference on New Technologies in Teaching and Learning Chinese, 501–11. Citeseer.Google Scholar
Daley, S. G., and Rappolt-Schlichtmann, G.. 2018. ‘Stigma Consciousness Among Adolescents With Learning Disabilities: Considering Individual Experiences of Being Stereotyped’. Learning Disability Quarterly 41 (4): 200–12. https://doi.org/10.1177/0731948718785565.Google Scholar
Dann, H.-D., Diegritz, T., and Rosenbusch, H. S.. 1999. Gruppenunterricht im Schulalltag: Realität und Chancen. Universitätsbibliothek.Google Scholar
David Hill, W., Hagenaars, S. P., Marioni, R. E., et al. 2016. ‘Molecular Genetic Contributions to Social Deprivation and Household Income in UK Biobank’. Current Biology: CB 26 (22): 3083–9.Google Scholar
Davidson, K., Eng, K., and Barner, D.. 2012. ‘Does Learning to Count Involve a Semantic Induction?’ Cognition 123 (1): 162–73.Google Scholar
Deary, I. 2003. ‘Population Sex Differences in IQ at Age 11: The Scottish Mental Survey 1932’. Intelligence 31 (6): 533–42. https://doi.org/10.1016/s0160-2896(03)00053-9.Google Scholar
Deater-Deckard, K. 2014. ‘Family Matters: Intergenerational and Interpersonal Processes of Executive Function and Attentive Behavior’. Current Directions in Psychological Science 23 (3): 230–6.Google Scholar
DeFrancis, J. 1989. Visible Speech: The Diverse Oneness of Writing Systems. University of Hawaii Press.CrossRefGoogle Scholar
Dehaene, S. 1992. ‘Varieties of Numerical Abilities’. Cognition 44 (1-2): 1–42.Google Scholar
Dehaene, S., and Cohen, L.. 2007. ‘Cultural Recycling of Cortical Maps’. Neuron 56 (2): 384–98.Google Scholar
Dehaene, S., Pegado, F., Braga, L. W., et al. 2010. ‘How Learning to Read Changes the Cortical Networks for Vision and Language’. Science 330 (6009): 1359–64.Google Scholar
Déjerine, J. 1891. ‘Sur Un Cas de Cécité Verbale Avec Agraphie Suivi D’autopsie’. Mémoires de La Société de Biologie 3: 197–201.Google Scholar
De Jong, P. F., and Van der Leij, A.. 1999. ‘Specific Contributions of Phonological Abilities to Early Reading Acquisition: Results from a Dutch Latent Variable Longitudinal Study’. Specific Contributions of Phonological Abilities to Early Reading Acquisition: Results from a Dutch Latent Variable Longitudinal Study 91 (3): 450.Google Scholar
Deming, D. 2009. ‘Early Childhood Intervention and Life-Cycle Skill Development: Evidence from Head Start’. American Economic Journal. Applied Economics 1 (3): 111–34.Google Scholar
Deno, S. L. 1985. ‘Curriculum-Based Measurement: The Emerging Alternative’. Exceptional Children 52, 219–232 https://doi.org/10.1177/001440298505200303.Google Scholar
Desoete, A., Roeyers, H., and De Clercq, A.. 2004. ‘Children with Mathematics Learning Disabilities in Belgium’. Journal of Learning Disabilities 37 (1): 50–61.Google Scholar
D’Esposito, M., and Postle, B. R.. 2015. ‘The Cognitive Neuroscience of Working Memory’. Annual Review of Psychology. https://doi.org/10.1146/annurev-psych-010814-015031.CrossRefGoogle Scholar
Devine, A., Soltész, F., Nobes, A., Goswami, U., and Szűcs, D.. 2013. ‘Gender Differences in Developmental Dyscalculia Depend on Diagnostic Criteria’. Learning and Instruction 27 (October): 31–9.CrossRefGoogle ScholarPubMed
DeWitt, I., and Rauschecker, J. P.. 2012. ‘Phoneme and Word Recognition in the Auditory Ventral Stream’. Proceedings of the National Academy of Sciences of the United States of America 109 (8): E505–14.Google Scholar
Diamanti, V., Goulandris, N., Campbell, R., and Protopapas, A.. 2018. ‘Dyslexia Profiles Across Orthographies Differing in Transparency: An Evaluation of Theoretical Predictions Contrasting English and Greek’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 22 (1): 55–69.Google Scholar
Diamond, A., and Ling, D. S.. 2016. ‘Conclusions about Interventions, Programs, and Approaches for Improving Executive Functions That Appear Justified and Those That, despite Much Hype, Do Not’. Developmental Cognitive Neuroscience 18 (April): 34–48.Google Scholar
Di Ianni, M., Wilsher, C. R., Blank, M. S., et al. 1985. ‘The Effects of Piracetam in Children with Dyslexia’. Journal of Clinical Psychopharmacology 5 (5): 272–8.Google Scholar
Dilling, H., and Freyberger, H. J.. 2019. Taschenführer Zur ICD-10-Klassifikation Psychischer Störungen.CrossRefGoogle Scholar
Dilnot, J., Hamilton, L., Maughan, B., and Snowling, M.J.. 2017. ‘Child and Environmental Risk Factors Predicting Readiness for Learning in Children at High Risk of Dyslexia’. Development and Psychopathology 29 (1): 235–44.Google Scholar
Dinkel, P. J., Willmes, K., Krinzinger, H., Konrad, K., and Koten Jr, J. W.. 2013. ‘Diagnosing Developmental Dyscalculia on the Basis of Reliable Single Case FMRI Methods: Promises and Limitations’. PloS One 8 (12): e83722.Google Scholar
Döhnert, M., and Englert, E. D.. 2003. ‘Das Irlen-Syndrom – Gibt Es Pathophysiologische Korrelate Und Wissenschaftliche Evidenz Für Das “Lesen Mit Farben”?’ Zeitschrift Fur Kinder- Und Jugendpsychiatrie Und Psychotherapie 31 (4): 305–9.Google Scholar
Dolean, D., Melby-Lervåg, M., Tincas, I., Damsa, C., and Lervåg, A. O.. 2019. ‘Achievement Gap: Socioeconomic Status Affects Reading Development beyond Language and Cognition in Children Facing Poverty’. Learning and Instruction 63 (October): 101218.Google Scholar
Dowker, A. 2004. ‘What Works for Children with Mathematical Difficulties?,’ January. www.researchgate.net/publication/253032270.Google Scholar
Dowker, A. 2019. Individual Differences in Arithmetic: Implications for Psychology, Neuroscience and Education. Routledge.Google Scholar
Dowker, A., and Nuerk, H.-C.. 2016. ‘Editorial: Linguistic Influences on Mathematics’. Frontiers in Psychology 7 (July): 1035.Google Scholar
Dudley-Marling, C. 2004. ‘The Social Construction of Learning Disabilities’. Journal of Learning Disabilities 37 (6): 482–9.Google Scholar
Dumas, D., McNeish, D., Sarama, J., and Clements, D.. 2019. ‘Preschool Mathematics Intervention Can Significantly Improve Student Learning Trajectories Through Elementary School’. AERA Open 5 (4). https://doi.org/10.1177/2332858419879446.Google Scholar
Duncan, G. J., Dowsett, C. J., Claessens, A., et al. 2007. ‘School Readiness and Later Achievement’. Developmental Psychology 43 (6): 1428–46. https://doi.org/10.1037/0012-1649.43.6.1428.Google Scholar
Duncan, R. J., Schmitt, S. A., and Lowe Vandell, D. 2019. ‘Additive and Synergistic Relations of Early Mother-Child and Caregiver-Child Interactions for Predicting Later Achievement’. Developmental Psychology 55 (12): 2522–33.Google Scholar
Dunn, L. M. 1968. ‘Special Education for the Mildly Retarded – Is Much of It Justifiable?’ Exceptional Children 35 (1): 5–22.Google Scholar
Ebbinghaus, H. 1885. Über das Gedächtnis: Untersuchungen zur experimentellen Psychologie. Duncker & Humblot.Google Scholar
Education Equity Research Initiative. 2017. ‘Mainstreaming Equity in Education’. Education Equity Research Initiative. October 27, 2017. www.fhi360.org/sites/default/files/media/documents/resource-mainstreaming-equity-education.pdf.Google Scholar
‘Education Policy Outlook in Norway’. 2020. OECD Education Policy Perspectives. Organisation for Economic Co-Operation and Development (OECD). https://doi.org/10.1787/8a042924-en.Google Scholar
Ehlert, A., and Fritz, A.. 2013. ‘Evaluation of Maths Training Programme for Children with Learning Difficulties’. South African Journal of Childhood Education 3 (1): 117–40.Google Scholar
Ehlert, A., Schroeders, U., and Fritz-Stratmann, A.. 2012. ‘Kritik Am Diskrepanzkriterium in Der Diagnostik von Legasthenie Und Dyskalkulie’. Lernen Und Lernstörungen 1 (3): 169–84. https://doi.org/10.1024/2235-0977/a000018.Google Scholar
Ehri, L. C., Nunes, S. R., Stahl, S. A., and Willows, D. M.. 2001. ‘Systematic Phonics Instruction Helps Students Learn to Read: Evidence from the National Reading Panel’s Meta-Analysis’. Review of Educational Research 71 (3): 393–447.Google Scholar
Ehri, L. C., Nunes, S. R., Willows, D. M., et al. 2001. ‘Phonemic Awareness Instruction Helps Children Learn to Read: Evidence From the National Reading Panel’s Meta-Analysis’. Reading Research Quarterly 36 (3): 250–87. https://doi.org/10.1598/rrq.36.3.2.Google Scholar
Eimeren, L. van, Niogi, S. N., McCandliss, B. D., Holloway, I. D., and Ansari, D.. 2008. ‘White Matter Microstructures Underlying Mathematical Abilities in Children’. Neuroreport 19 (11): 1117–21.Google Scholar
Einarsdóttir, J. T., Björnsdóttir, A., and Símonardóttir, I.. 2016. ‘The Predictive Value of Preschool Language Assessments on Academic Achievement: A 10-Year Longitudinal Study of Icelandic Children’. American Journal of Speech-Language Pathology / American Speech-Language-Hearing Association 25 (1): 67–79.Google Scholar
Elbro, C., and Petersen, D. K.. 2004. ‘Long-Term Effects of Phoneme Awareness and Letter Sound Training: An Intervention Study With Children at Risk for Dyslexia’. Journal of Educational Psychology 96 (4): 660–70. https://doi.org/10.1037/0022-0663.96.4.660.Google Scholar
Elder, T., Figlio, D., Imberman, S., and Persico, C.. 2019. ‘School Segregation and Racial Gaps in Special Education Identification’. National Bureau of Economic Research. https://doi.org/10.3386/w25829.Google Scholar
Eliot, Lise. 2011. ‘The Trouble with Sex Differences’. Neuron 72 (6): P895–8. https://doi.org/10.1016/j.neuron.2011.12.001.Google Scholar
Elliott, J. G., and Grigorenko, E. L.. 2014. The Dyslexia Debate. Cambridge University Press.Google Scholar
Elliott, L., Feigenson, L., Halberda, J., and Libertus, M. E.. 2019. ‘Bidirectional, Longitudinal Associations between Math Ability and Approximate Number System Precision in Childhood’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 20 (1): 56–74.Google Scholar
Else-Quest, N. M., Hyde, J. S., and Linn, M. C.. 2010. ‘Cross-National Patterns of Gender Differences in Mathematics: A Meta-Analysis’. Psychological Bulletin 136 (1): 103–27.Google Scholar
Engle, P. L., Black, M. M., Behrman, J. R., et al. 2007. ‘Strategies to Avoid the Loss of Developmental Potential in More than 200 Million Children in the Developing World’. The Lancet 369 (9557): 229–42.Google Scholar
Ennemoser, M., Marx, P, Weber, J., and Schneider, W.. 2012. ‘Spezifische Vorläuferfertigkeiten Der Lesegeschwindigkeit, Des Leseverständnisses Und Des Rechtschreibens’. Zeitschrift Fur Entwicklungspsychologie Und Padagogische Psychologie 44 (2): 53–67.Google Scholar
Erbeli, F., Hart, S. A., Wagner, R. K., and Taylor, J.. 2018. ‘Examining the Etiology of Reading Disability as Conceptualized by the Hybrid Model’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 22 (2): 167–80.Google Scholar
‘Ernst Klett Verlag – Zahlenbuch – Frühförderprogramm Ausgabe Ab 2009 – Lehrwerk Konzeption’. n.d. Accessed July 29, 2021. https://www.klett.de/lehrwerk/zahlenbuch-fruehfoerderprogramm-ausgabe-ab-2009/konzeption.Google Scholar
Espinoza, O. 2007. ‘Solving the Equity–equality Conceptual Dilemma: A New Model for Analysis of the Educational Process’. Educational Research 49 (4): 343–63. https://doi.org/10.1080/00131880701717198.Google Scholar
European Commission/EACEA/Eurydice (2020). Compulsory Education in Europe – 2020/21. Eurydice Facts and Figures. Luxembourg: Publications Office of the European Union. Retrieved from https://eacea.ec.europa.eu/national-policies/eurydice/content/compulsory-education-europe-202021_en.Google Scholar
Evans, B. J. W., Patel, R, Wilkins, A. J., et al. 2008. ‘A Review of the Management of 323 Consecutive Patients Seen in a Specific Learning Difficulties Clinic’. Ophthalmic & Physiological Optics: The Journal of the British College of Ophthalmic Opticians 19 (6): 454–66.Google Scholar
Eyal, G. 2013. ‘For a Sociology of Expertise: The Social Origins of the Autism Epidemic’. The American Journal of Sociology 118 (4): 863–907.Google Scholar
Fan, J., Mccandliss, B., Fossella, J., Flombaum, J., and Posner, M.. 2005. ‘The Activation of Attentional Networks’. NeuroImage 26 (2): 471–9. https://doi.org/10.1016/j.neuroimage.2005.02.004.Google Scholar
Faramarzi, S., Yarmohamadian, A., Malekpour, M., Shirzadi, P., and Qasemi, M.. 2016. ‘The Effect of Neuropsychological Interventions on Language Performance in Preschool Children with Specific Language Impairment (SLI): A Case Study’. Middle Eastern Journal of Disability Studies 6: 304–16.Google Scholar
Farmer, M. E., and Klein, R. M.. 1995. ‘The Evidence for a Temporal Processing Deficit Linked to Dyslexia: A Review’. Psychonomic Bulletin & Review 2 (4): 460–93.Google Scholar
Farrington-Flint, L., Vanuxem-Cotterill, S., and Stiller, J.. 2009. ‘Patterns of Problem-Solving in Children’s Literacy and Arithmetic’. British Journal of Developmental Psychology 27 (4): 815–34. https://doi.org/10.1348/026151008x383148.Google Scholar
Fawcett, A. J. 2002. ‘Dyslexia, the Cerebellum and Phonological Skill’. In Basic Functions of Language, Reading and Reading Disability, edited by Witruk, E., Friederici, A. D., and Lachmann, T., 265–79. Springer US.Google Scholar
Feingold, A. 1994. ‘Gender Differences in Variability in Intellectual Abilities: A Cross-Cultural Perspective’. Sex Roles 30 (1): 81–92.Google Scholar
Feng, J., Spence, I., and Pratt, J.. 2007. ‘Playing an Action Video Game Reduces Gender Differences in Spatial Cognition’. Psychological Science 18 (10): 850–5.Google Scholar
Ferraz, E., Dos Santos Gonçalves, T, Freire, T., et al. 2018. ‘Effects of a Phonological Reading and Writing Remediation Program in Students with Dyslexia: Intervention for Specific Learning Disabilities’. Folia Phoniatrica et Logopaedica: Official Organ of the International Association of Logopedics and Phoniatrics 70 (2): 59–73.Google Scholar
Fertonani, A., Ferrari, C., and Miniussi, C.. 2015. ‘What Do You Feel If I Apply Transcranial Electric Stimulation? Safety, Sensations and Secondary Induced Effects’. Clinical Neurophysiology 126 (11): 2181–8. https://doi.org/10.1016/j.clinph.2015.03.015.Google Scholar
Fiez, J. A., Balota, D. A., Raichle, M. E., and Petersen, S. E.. 1999. ‘Effects of Lexicality, Frequency, and Spelling-to-Sound Consistency on the Functional Anatomy of Reading’. Neuron 24 (1): P205–218. https://doi.org/10.1016/s0896-6273(00)80833-8.Google Scholar
Finisguerra, A., Borgatti, R., and Urgesi, C.. 2019. ‘Non-Invasive Brain Stimulation for the Rehabilitation of Children and Adolescents With Neurodevelopmental Disorders: A Systematic Review’. Frontiers in Psychology 10 (February): 135.Google Scholar
Fiori, V., Coccia, M, Marinelli, C. V., et al. 2011. ‘Transcranial Direct Current Stimulation Improves Word Retrieval in Healthy and Nonfluent Aphasic Subjects’. Journal of Cognitive Neuroscience 23 (9): 2309–23.Google Scholar
Fischbach, A., Schuchardt, K., Brandenburg, J., et al. 2013. ‘Prävalenz von Lernschwächen Und Lernstörungen: Zur Bedeutung Der Diagnosekriterien’. Lernen Und Lernstörungen 2 (2): 65–76.Google Scholar
Fischer, F. W., Liberman, I. Y., and Shankweiler, D.. 1978. ‘Reading Reversals and Developmental Dyslexia: A Further Study’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 14 (4): 496–510.Google Scholar
Fischer, M. Y., and Pfost, M.. 2015. ‘Wie Effektiv Sind Maßnahmen Zur Förderung Der Phonologischen Bewusstheit?’ Zeitschrift Für Entwicklungspsychologie Und Pädagogische Psychologie 47: 35–51. https://doi.org/10.1026/0049-8637/a000121.Google Scholar
Fishbein, B., Martin, M. O., Mullis, I. V. S., and Foy, P.. 2018. ‘The TIMSS 2019 Item Equivalence Study: Examining Mode Effects for Computer-Based Assessment and Implications for Measuring Trends’. Large-Scale Assessments in Education 6 (11). https://doi.org/10.1186/s40536-018-0064-z.Google Scholar
Fish, R. E. 2017. ‘The Racialized Construction of Exceptionality: Experimental Evidence of Race/ethnicity Effects on Teachers’ Interventions’. Social Science Research 62 (February): 317–34.Google Scholar
Fish, R. E 2019. ‘Standing Out and Sorting In: Exploring the Role of Racial Composition in Racial Disparities in Special Education’. American Educational Research Journal 56 (6): 2573–608.Google Scholar
Fish, R. E 2022. “Stratified Medicalization of Children’s Schooling Difficulties.” Paper presented at the Interdisciplinary Training Program Fellows Conference, University of Wisconsin.Google Scholar
Fivush, R., and Nelson, K.. 2004. ‘Culture and Language in the Emergence of Autobiographical Memory’. Psychological Science 15 (9): 573–7.Google Scholar
Flannery, K. A., Liederman, J., Daly, L., and Schultz, J.. 2000. ‘Male Prevalence for Reading Disability Is Found in a Large Sample of Black and White Children Free from Ascertainment Bias’. Journal of the International Neuropsychological Society 6 (4): 433–420. https://doi.org/10.1017/s1355617700644016.Google Scholar
Fletcher, J. M., Savage, R., and Vaughn, S.. 2020. ‘A Commentary on Bowers (2020) and the Role of Phonics Instruction in Reading’. Educational Psychology Review 33: 1249–74. November. https://doi.org/10.1007/s10648-020-09580-8.Google Scholar
Flowers, L., Meyer, M., Lovato, J., Wood, F., and Felton, R.. 2001. ‘Does Third Grade Discrepancy Status Predict the Course of Reading Development?’ Annals of Dyslexia 51 (1): 49–71.CrossRefGoogle Scholar
‘Förderboxen Für KiTa Und Anfangsunterricht – Mengen, Zählen, Zahlen (MZZ) – Die Welt Der Mathematik Verstehen – Koffer Mit Fördermaterialien Und Handreichungen (80 S.)’. n.d. Accessed 24 August 2021. /www.cornelsen.de/produkte/foerderboxen-fuer-kita-und-anfangsunterricht-mengen-zaehlen-zahlen-mzz-die-welt-der-mathematik-verstehen-koffer-mit-foerdermaterialien-und-handreichungen-80-s-9783060800155.Google Scholar
Foy, J. G., and Mann, V. A.. 2013. ‘Executive Function and Early Reading Skills’. Reading and Writing 26 (3): 453–72.Google Scholar
Francis, D. J., Fletcher, J. M., Stuebing, K. K., et al. 2005. ‘Psychometric Approaches to the Identification of LD’. Journal of Learning Disabilities 38 (2): 98–108. https://doi.org/10.1177/00222194050380020101.Google Scholar
Franco, A., Malhotra, N., and Simonovits, G.. 2014. ‘Social Science. Publication Bias in the Social Sciences: Unlocking the File Drawer’. Science 345 (6203): 1502–5.Google Scholar
Frankland, P. W., Köhler, S., and Josselyn, S. A.. 2013. ‘Hippocampal Neurogenesis and Forgetting’. Trends in Neurosciences 36 (9): 497–503.Google Scholar
Frederick, A., and Shifrer, D.. 2019. ‘Race and Disability: From Analogy to Intersectionality’. Sociology of Race and Ethnicity 5 (2): 200–14.Google Scholar
Fredricks, J. A., and Eccles, J. S.. 2002. ‘Children’s Competence and Value Beliefs from Childhood through Adolescence: Growth Trajectories in Two Male-Sex-Typed Domains’. Developmental Psychology 38 (4): 519–33.Google Scholar
Freud, S. 1924. A General Introduction to Psychoanalysis. Washington Square Press.Google Scholar
Frick, A. 2019. ‘Spatial Transformation Abilities and Their Relation to Later Mathematics Performance’. Psychological Research 83 (7): 1465–84.Google Scholar
Friso-van den Bos, I., Kroesbergen, E. H., Van Luit, J. E. H., et al. 2015. ‘Longitudinal Development of Number Line Estimation and Mathematics Performance in Primary School Children’. Journal of Experimental Child Psychology 134 (June): 12–29.Google Scholar
Frith, U. 2017. ‘Beneath the Surface of Developmental Dyslexia’. In Surface Dyslexia. Routledge. https://doi.org/10.4324/9781315108346-18.Google Scholar
Frith, U. 1999. ‘Paradoxes in the Definition of Dyslexia’. Dyslexia 5 (4): 192–214.3.0.CO;2-N>CrossRefGoogle Scholar
Froehlich, T. E., Fogler, J, Barbaresi, W. J., et al. 2018. ‘Using ADHD Medications to Treat Coexisting ADHD and Reading Disorders: A Systematic Review’. Clinical Pharmacology and Therapeutics 104 (4): 619–37.CrossRefGoogle ScholarPubMed
Fuchs, L. S., Compton, D. L., Fuchs, D., et al. 2005. ‘The Prevention, Identification, and Cognitive Determinants of Math Difficulty’. Journal of Educational Psychology 97 (3): 493–513.Google Scholar
Fuchs, L. S., and Fuchs, D.. 1986. ‘Effects of Systematic Formative Evaluation: A Meta-Analysis’. Exceptional Children 53 (3): 199–208. https://doi.org/10.1177/001440298605300301.Google Scholar
Fuchs, L. S., Fuchs, D., Compton, D. L., et al. 2006. ‘The Cognitive Correlates of Third-Grade Skill in Arithmetic, Algorithmic Computation, and Arithmetic Word Problems’. Journal of Educational Psychology 98 (1): 29–43.Google Scholar
Fuchs, L. S., Fuchs, D., Hamlett, C. L., Hope, S. K., et al. 2006. ‘Extending Responsiveness-to-Intervention to Math Problem-Solving at Third Grade’. TEACHING Exceptional Children 38 (4): 59–63. https://doi.org/10.1177/004005990603800409.Google Scholar
Fuchs, L. S., Powell, S. R., Seethaler, P. M., et al. ‘The Effects of Strategic Counting Instruction, with and without Deliberate Practice, on Number Combination Skill among Students with Mathematics Difficulties’. Learning and Individual Differences 20 (2): 89–100.CrossRefGoogle Scholar
Fuhs, M. W., and McNeil, N. M.. 2013. ‘ANS Acuity and Mathematics Ability in Preschoolers from Low-Income Homes: Contributions of Inhibitory Control’. Developmental Science 16 (1): 136–48.Google Scholar
Fuhs, M. W., Turner Nesbitt, K, Clark Farran, D, and Dong, N.. 2014. ‘Longitudinal Associations between Executive Functioning and Academic Skills across Content Areas’. Developmental Psychology 50 (6): 1698–709.Google Scholar
Fuhs, M. W., Tavassolie, N., Wang, Y., et al. 2021. ‘Children’s Flexible Attention to Numerical and Spatial Magnitudes in Early Childhood’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 22 (1): 22–47.Google Scholar
Furman, T., and Rubinsten, O.. 2012. ‘Symbolic and Non Symbolic Numerical Representation in Adults with and without Developmental Dyscalculia’. Behavioral and Brain Functions: BBF 8 (November): 55.Google Scholar
Furnes, B., and Samuelsson, S.. 2009. ‘Preschool Cognitive and Language Skills Predicting Kindergarten and Grade 1 Reading and Spelling: A Cross-Linguistic Comparison’. Journal of Research in Reading 32 (3): 275–92.CrossRefGoogle Scholar
Furnes, B., and Samuelsson, S. 2011. ‘Phonological Awareness and Rapid Automatized Naming Predicting Early Development in Reading and Spelling: Results from a Cross-Linguistic Longitudinal Study’. Learning and Individual Differences 21 (1): 85–95.CrossRefGoogle ScholarPubMed
Gabel, S. L., Curcic, S, Powell, J. J. W., Khader, K., and Albee, L.. 2009. ‘Migration and Ethnic Group Disproportionality in Special Education: An Exploratory Study’. Disability & Society 24 (5): 625–39.Google Scholar
Gabrieli, J. D. E. 2009. ‘Dyslexia: A New Synergy between Education and Cognitive Neuroscience’. Science 325 (5938): 280–3.Google Scholar
Galaburda, A. M. 1993. ‘Neurology of Developmental Dyslexia’. Current Opinion in Neurobiology 3 (2): 237–42.Google Scholar
Galaburda, A. M. (2018). The Role of Rodent Models in Dyslexia Research: Understanding the Brain, Sex Differences, Lateralization, and Behavior. In T. Lachmann & T. Weis (Eds.), Literacy Studies. Reading and Dyslexia (Vol. 16, pp. 83–102). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-90805-2_5Google Scholar
Galaburda, A. M., Sherman, G. F., Rosen, G. D., Aboitiz, F., and Geschwind, N.. 1985. ‘Developmental Dyslexia: Four Consecutive Patients with Cortical Anomalies’. Annals of Neurology 18 (2): 222–33.Google Scholar
Gallagher, A., Frith, U., and Snowling, M. J.. 2000. ‘Precursors of Literacy Delay among Children at Genetic Risk of Dyslexia’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 41 (2): 203–13.Google Scholar
Galuschka, K., Görgen, R, Kalmar, J, et al. 2020. ‘Effectiveness of Spelling Interventions for Learners with Dyslexia: A Meta-Analysis and Systematic Review’. Educational Psychologist 55 (1): 1–20.Google Scholar
Galuschka, K., Ise, E., Krick, K., and Schulte-Körne, G.. 2014. ‘Effectiveness of Treatment Approaches for Children and Adolescents with Reading Disabilities: A Meta-Analysis of Randomized Controlled Trials’. PloS One 9 (2): e89900.Google Scholar
Garland-Thomson, R. 2020. ‘Integrating Disability, Transforming Feminist Theory’. In McCann, C. R., Kim, S.-K., Ergun, E (eds.) Feminist Theory Reader. https://doi.org/10.4324/9781003001201-22.Google Scholar
Gathercole, S. E., and Baddeley, A. D.. 2014. Working Memory and Language. Psychology Press.CrossRefGoogle Scholar
Geary, D. C. 1989. ‘A Model for Representing Gender Differences in the Pattern of Cognitive Abilities’. The American Psychologist 44 (8): 1155–6.Google Scholar
Geary, D. C. 2010. ‘Missouri Longitudinal Study of Mathematical Development and Disability’. In BJEP Monograph Series II, Number 7-Understanding Number Development and Difficulties, 31:31–49. British Psychological Society.Google Scholar
Geary, D. C. 2011. ‘Cognitive Predictors of Achievement Growth in Mathematics: A 5-Year Longitudinal Study’. Developmental Psychology 47 (6): 1539–52.Google Scholar
Geary, D. C. n.d. ‘Missouri Longitudinal Study of Mathematical Development and Disability’. Accessed July 23, 2021. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.473.6330.Google Scholar
Geary, D. C., Berch, D. B., and Koepke, K. M.. 2014. Evolutionary Origins and Early Development of Number Processing. Academic Press.Google Scholar
Geary, D. C., and vanMarle, K.. 2018. ‘Growth of Symbolic Number Knowledge Accelerates after Children Understand Cardinality’. Cognition 177 (August): 69–78.Google Scholar
Geary, D. C. 1993. ‘Mathematical Disabilities: Cognitive, Neuropsychological, and Genetic Components’. Psychological Bulletin 114 (2): 345–62.CrossRefGoogle ScholarPubMed
Geeler, S. K., Grob, U., Heinze, A., et al. 2021. ‘Längsschnittliche Messung Numerischer Kompetenzen von Kindergartenkindern’. Diagnostica 67 (2): 62–74.Google Scholar
Geiger, E. F., and Brewster, M. E.. 2018. ‘Development and Evaluation of the Individuals With Learning Disabilities And/or Difficulties Perceived Discrimination Scale’. The Counseling Psychologist 46 (6): 708–37. https://doi.org/10.1177/0011000018794919.CrossRefGoogle Scholar
Gelfand, J. R., and Bookheimer, S. Y.. 2003. ‘Dissociating Neural Mechanisms of Temporal Sequencing and Processing Phonemes’. Neuron 38 (5): P831–42. https://doi.org/10.1016/s0896-6273(03)00285-x.CrossRefGoogle ScholarPubMed
Georgiou, G. K., and Parrila, R.. 2020. ‘What Mechanism Underlies the Rapid Automatized Naming–reading Relation?’ Journal of Experimental Child Psychology 194 (June): 104840.Google Scholar
Gerber, M. M. 2005. ‘Teachers Are Still the Test: Limitations of Response to Instruction Strategies for Identifying Children with Learning Disabilities’. Journal of Learning Disabilities 38 (6): 516–24.Google Scholar
Gerlach, M., Fritz, A, Ricken, G, and Schmidt, S. 2007. Kalkulie. Diagnose- und Trainingsprogramm für rechenschwache Kinder. [Kalkulie. Diagnostic and Training]. https://www.cornelsen.de/reihen/kalkulie-diagnose-und-trainingsprogramm-fuer-rechenschwache-kinder-360002290000.Google Scholar
Gerlach, M., Fritz, A., and Leutner, D.. 2013. Mathematik- und Rechenkonzepte im Vor- und Grundschulalter – Training: MARKO-T; Manual. Hogrefe.Google Scholar
Gersten, R., Chard, D. J., Jayanthi, M, et al. 2009. ‘Mathematics Instruction for Students With Learning Disabilities: A Meta-Analysis of Instructional Components’. Review of Educational Research 79 (3): 1202–42.Google Scholar
Gibbs, S. J., and Elliott, J. G.. 2020. ‘The Dyslexia Debate: Life without the Label’. Oxford Review of Education 46 (4): 487–500.CrossRefGoogle Scholar
Gibson, D. J., Gunderson, E. A., and Levine, S. C.. 2020. ‘Causal Effects of Parent Number Talk on Preschoolers’ Number Knowledge’. Child Development 91 (6): e1162–77.Google Scholar
Gilmore, C., Attridge, N., Clayton, S., et al. 2013. ‘Individual Differences in Inhibitory Control, Not Non-Verbal Number Acuity, Correlate with Mathematics Achievement’. PloS One 8 (6): e67374.Google Scholar
Ginsburg, A., and Smith, M. S.. 2016. ‘Do Randomized Controlled Trials Meet the “Gold Standard”’. American Enterprise Institute. www.carnegiefoundation.org/wp-content/uploads/2016/03/Do-randomized-controlled-trials-meet-the-gold-standard.pdf.Google Scholar
Giofrè, D., Cumming, G., Fresc, L., Boedker, I., and Tressoldi, P.. 2017. ‘The Influence of Journal Submission Guidelines on Authors’ Reporting of Statistics and Use of Open Research Practices’. PloS One 12 (4): e0175583.Google Scholar
Given, B. K., Wasserman, J. D., Chari, S. A., Beattie, K., and Eden, G. F.. 2008. ‘A Randomized, Controlled Study of Computer-Based Intervention in Middle School Struggling Readers’. Brain and Language 106 (2): 83–97.Google Scholar
Göbel, S. M., Moeller, K., Pixner, S., Kaufmann, L., and Nuerk, H.-C.. 2014. ‘Language Affects Symbolic Arithmetic in Children: The Case of Number Word Inversion’. Journal of Experimental Child Psychology 119 (March): 17–25.Google Scholar
Goldin-Meadow, S., Levine, S. C., Hedges, L. V., et al. 2014. ‘New Evidence about Language and Cognitive Development Based on a Longitudinal Study: Hypotheses for Intervention’. The American Psychologist 69 (6): 588–99.Google Scholar
Golinkoff, R. M., Can, D. D., Soderstrom, M., and Hirsh-Pasek, K.. 2015. ‘(Baby)Talk to Me: The Social Context of Infant-Directed Speech and Its Effects on Early Language Acquisition’. Current Directions in Psychological Science 24 (5): 339–44.Google Scholar
González, J. E. J., and Garcia Espínel, A. I.. 1999. ‘Is IQ-Achievement Discrepancy Relevant in the Definition of Arithmetic Learning Disabilities?’ Learning Disability Quarterly: Journal of the Division for Children with Learning Disabilities 22 (4): 291–301.Google Scholar
Goodwin, A. P., and Ahn, S.. 2010. ‘A Meta-Analysis of Morphological Interventions: Effects on Literacy Achievement of Children with Literacy Difficulties’. Annals of Dyslexia 60 (2): 183–208.Google Scholar
Goodwin, A. P., and Ahn, S. 2013. ‘A Meta-Analysis of Morphological Interventions in English: Effects on Literacy Outcomes for School-Age Children’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 17 (4): 257–85.CrossRefGoogle Scholar
Gordanier, J., Ozturk, O., Williams, B., and Zhan, C.. 2020. ‘Free Lunch for All! The Effect of the Community Eligibility Provision on Academic Outcomes’. Economics of Education Review 77 (August): 101999.CrossRefGoogle Scholar
Görgen, R., De Simone, E., Schulte-Körne, G., and Moll, K.. 2021. ‘Predictors of Reading and Spelling Skills in German: The Role of Morphological Awareness’. Journal of Research in Reading 44 (1): 210–27.Google Scholar
Görgen, R., Huemer, S., Schulte-Körne, G., and Moll, K.. 2020. ‘Evaluation of a Digital Game-Based Reading Training for German Children with Reading Disorder’. Computers & Education 150 (June): 103834.Google Scholar
Goswami, U., and Bryant, P.. 2016. Phonological Skills and Learning to Read. Psychology Press.Google Scholar
Goswami, U., Ziegler, J. C., and Richardson, U.. 2005. ‘The Effects of Spelling Consistency on Phonological Awareness: A Comparison of English and German’. Journal of Experimental Child Psychology 92 (4): 345–65.Google Scholar
Gottlieb, J., Alter, M, Gottlieb, B. W., and Wishner, J.. 1994. ‘Special Education in Urban America: It’s Not Justifiable for Many’. The Journal of Special Education 27 (4): 453–65.Google Scholar
Gough, P. B., and Tunmer, W. E.. 1986. ‘Decoding, Reading and Reading Disability: Remedial and Special Education’. Remedial and Special Education 7(1): 6–10. doi:10.1177/074193258600700104.CrossRefGoogle Scholar
Goulandris, N. K., Snowling, M. J., and Walker, I.. 2000. ‘Is Dyslexia a Form of Specific Language Impairment? A Comparison of Dyslexic and Language Impaired Children as Adolescents’. Annals of Dyslexia 50 (1): 103–20.Google Scholar
Graham, L., and Pegg, J. E.. 2010. ‘Hard Data to Support the Effectiveness of ‘QuickSmart’ Numeracy’. https://rune.une.edu.au/web/handle/1959.11/7389.Google Scholar
Graham, L., and Pegg, J. E. 2011. ‘Evaluating the QuickSmart Numeracy Program: An Effective Australian Intervention That Improves Student Achievement, Responds to Special Educational Needs, and Fosters Teacher Collaboration’. The Journal of Educational Administration 29(2): 87–102.Google Scholar
Groen, O. van der, and Wenderoth, N.. 2016. ‘Transcranial Random Noise Stimulation of Visual Cortex: Stochastic Resonance Enhances Central Mechanisms of Perception’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 36 (19): 5289–98.Google Scholar
Gross-Tsur, V., Manor, O., and Shalev, R. S.. 1996. ‘Developmental Dyscalculia: Prevalence and Demographic Features’. Developmental Medicine & Child Neurology 38 (1): 25–33.CrossRefGoogle ScholarPubMed
Grube, D., and Hasselhorn, M.. 2006. Längsschnittliche Analysen Zur Lese-, Rechtschreib-Und Mathematikleistung Im Grundschulalter: Zur Rolle von Vorwissen, Intelligenz, Phonologischem Arbeitsgedächtnis Und Phonologischer Bewusstheit. na.Google Scholar
Gualtieri, T., and Hicks, R. E.. 1991. ‘An Immunoreactive Theory of Selective Male Affliction’. In 1986 Annual Progress In Child Psychiatry. Routledge. https://doi.org/10.4324/9780203450499-13.Google Scholar
Guidi, L. G., Velayos-Baeza, A., Martinez-Garay, I., et al. 2018. ‘The Neuronal Migration Hypothesis of Dyslexia: A Critical Evaluation 30 Years on’. The European Journal of Neuroscience 48 (10): 3212–33.Google Scholar
Guiso, L., Monte, F., Sapienza, P., and Zingales, L.. 2008. ‘Culture, Gender, and Math’. Science 320 (5880): 1164.Google Scholar
Gunderson, E. A., and Levine, S. C.. 2011. ‘Some Types of Parent Number Talk Count More than Others: Relations between Parents’ Input and Children’s Cardinal-Number Knowledge’. Developmental Science 14 (5): 1021–32.Google Scholar
Gunderson, E. A., Daeun Park, E. A. Maloney, S. L. Beilock, and S. C. Levine, . 2018. ‘Reciprocal Relations among Motivational Frameworks, Math Anxiety, and Math Achievement in Early Elementary School’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 19 (1): 21–46.Google Scholar
Gunderson, E. A., Ramirez, G, Beilock, S. L., and Levine, S. C.. 2012. ‘The Relation between Spatial Skill and Early Number Knowledge: The Role of the Linear Number Line’. Developmental Psychology 48 (5): 1229–41.Google Scholar
Gunderson, Elizabeth A., Ramirez, Gerardo, Levine, Susan C., and Beilock, Sian L.. 2012. ‘The Role of Parents and Teachers in the Development of Gender-Related Math Attitudes’. Sex Roles 66: 153–66. https://doi.org/10.1007/s11199-011-9996-2.Google Scholar
Gustafson, S., Fälth, L., Svensson, I., Tjus, T., and Heimann, M.. 2011. ‘Effects of Three Interventions on the Reading Skills of Children With Reading Disabilities in Grade 2’. Journal of Learning Disabilities 44 (2): 123–35.Google Scholar
Gustafson, S., Ferreira, J., and Rönnberg, J.. 2007. ‘Phonological or Orthographic Training for Children with Phonological or Orthographic Decoding Deficits’. Dyslexia 13 (3): 211–29.Google Scholar
Gutkin, Terry B., and Reynolds, Cecil R.. 2008. The Handbook of School Psychology, 4th Edition. Wiley Global Education.Google Scholar
Halberda, J., and Feigenson, L.. 2008. ‘Developmental Change in the Acuity of the ‘Number Sense’: The Approximate Number System in 3-, 4-, 5-, and 6-Year-Olds and Adults’. Developmental Psychology 44 (5): 1457–65.Google Scholar
Halpern, D. F., Benbow, C. P., Geary, D. C., et al. 2007. ‘The Science of Sex Differences in Science and Mathematics’. Psychological Science in the Public Interest: A Journal of the American Psychological Society 8 (1): 1–51.Google Scholar
Haman, M., Lipowska, K., Soltanlou, M., et al. 2020. ‘The Plural Still Counts: Cross-Linguistic Study of the Symbolic Numerical Magnitude Comparison Task in Polish- and German-Speaking Preschoolers’. PsyArXiv. August 11.https://doi.org/10.31234/osf.io/ge8zq.Google Scholar
Hanf, K., & Scharpf, F. W. (1978). ‘Interorganizational Policy Making Limits to Coordination and Central Control. London, Beverly Hills Sage Publications. – References – Scientific Research Publishing’. Accessed July 29, 2021. https://www.scirp.org/reference/referencespapers.aspx?referenceid=2594690.Google Scholar
Hannon, B. 2014. ‘Are There Gender Differences in the Cognitive Components of Adult Reading Comprehension?’ Learning and Individual Differences 32: 69–79. https://doi.org/10.1016/j.lindif.2014.03.017.Google Scholar
Hannula, M. M., Lepola, J., and Lehtinen, E.. 2010. ‘Spontaneous Focusing on Numerosity as a Domain-Specific Predictor of Arithmetical Skills’. Journal of Experimental Child Psychology 107 (4): 394–406.Google Scholar
Hanushek, E. A., and Kimko, D. D.. 2000. ‘Schooling, Labor-Force Quality, and the Growth of Nations’. The American Economic Review 90 (5): 1184–208.Google Scholar
Harry, B., and Klingner, J.. 2007. ‘Discarding the Deficit Model’. Educational Leadership: Journal of the Department of Supervision and Curriculum Development, N.E.A 64 (5): 16.Google Scholar
Harry, B., and Klingner, J. 2014. Why Are So Many Minority Students in Special Education?, 2nd Edition. Teachers College Press.Google Scholar
Hasselhorn, M., Köller, O., Maaz, K., and Zimmer, K.. 2014. ‘Implementation Wirksamer Handlungskonzepte Im Bildungsbereich Als Forschungsaufgabe’. Psychologische Rundschau; Ueberblick Uber Die Fortschritte Der Psychologie in Deutschland, Oesterreich, Und Der Schweiz 65 (3): 140–4.Google Scholar
Hasselhorn, M., and Mähler, C.. 2006. ‘Diagnostik von Lernstörungen’. Handbuch Der Psychologischen Diagnostik, 618–25.Google Scholar
Hasselhorn, M., Schneider, W., and Trautwein, U., eds. 2014. Lernverlaufsdiagnostik. 1st ed. Jahrbuch der pädagogisch-psychologischen Diagnostik. Tests und Trends. Hogrefe Verlag.Google Scholar
Hatcher, P. J., Hulme, C., and Ellis, A. W.. 1994. ‘Ameliorating Early Reading Failure by Integrating the Teaching of Reading and Phonological Skills: The Phonological Linkage Hypothesis’. Child Development 65 (1): 41–57. https://doi.org/10.2307/1131364.Google Scholar
Hattie, J. 2008. Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. Routledge.Google Scholar
Hawes, Z., and Ansari, D.. 2020. ‘What Explains the Relationship between Spatial and Mathematical Skills? A Review of Evidence from Brain and Behavior’. Psychonomic Bulletin & Review 27 (3): 465–82.Google Scholar
Hawes, Z., Moss, J., Caswell, B., Naqvi, S., and MacKinnon, S.. 2017. ‘Enhancing Children’s Spatial and Numerical Skills through a Dynamic Spatial Approach to Early Geometry Instruction: Effects of a 32-Week Intervention’. Cognition and Instruction 35 (3): 236–64.Google Scholar
Hawes, Z., Nosworthy, N., Archibald, L., and Ansari, D.. 2019. ‘Kindergarten Children’s Symbolic Number Comparison Skills Relates to 1st Grade Mathematics Achievement: Evidence from a Two-Minute Paper-and-Pencil Test’. Learning and Instruction 59 (February): 21–33.Google Scholar
Hawke, J. L., Olson, R. K., Willcut, E. G., Wadsworth, S. J., and DeFries, J. C.. 2009. ‘Gender Ratios for Reading Difficulties’. Dyslexia 15 (3): 239–42. https://doi.org/10.1002/dys.389.Google Scholar
Hayashi, Y., Okita, H., Kinoshita, M., Miyashita, K., and Nakada, M.. 2014. ‘Functional Recovery from Pure Dyslexia with Preservation of Subcortical Association Fiber Networks’. Interdisciplinary Neurosurgery 1 (3): 59–62. https://doi.org/10.1016/j.inat.2014.06.004.Google Scholar
Hayek, M., Karni, A., and Eviatar, Z.. 2019. ‘Transcoding Number Words by Bilingual Speakers of Arabic: Writing Multi-Digit Numbers in a Units-Decades Inverting Language’. Writing Systems Research 11 (2): 188–202.Google Scholar
Hecht, S. A., Burgess, S. R., Torgesen, J. K., Wagner, R. K., and Rashotte, C. A.. 2000. ‘Explaining Social Class Differences in Growth of Reading Skills from Beginning Kindergarten through Fourth-Grade: The Role of Phonological Awareness, Rate of Access, and Print Knowledge’. Reading and Writing 12 (1): 99–128.Google Scholar
Heckman, J. J. 2012. ‘Invest in Early Childhood Development: Reduce Deficits, Strengthen the Economy’. The Heckman Equation 7: 1–2.Google Scholar
Hedges, L., and Nowell, A.. 1995. ‘Sex Differences in Mental Test Scores, Variability, and Numbers of High-Scoring Individuals’. Science 269 (5220): 41–5. https://doi.org/10.1126/science.7604277.Google Scholar
Heim, S., Tschierse, J., Amunts, K., et al. 2008. ‘Cognitive Subtypes of Dyslexia’. Acta Neurobiologiae Experimentalis 68 (1): 73–82.Google Scholar
Heine, A., Wissmann, J., Tamm, S., et al. 2013. ‘An Electrophysiological Investigation of Non-Symbolic Magnitude Processing: Numerical Distance Effects in Children with and without Mathematical Learning Disabilities’. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior 49 (8): 2162–77.Google Scholar
Hein, J., Bzufka, M. W., and Neumärker, K. J.. 2000. ‘The Specific Disorder of Arithmetic Skills. Prevalence Studies in a Rural and an Urban Population Sample and Their Clinico-Neuropsychological Validation’. European Child & Adolescent Psychiatry 9 Suppl 2: II87–101.CrossRefGoogle Scholar
Hellstrand, H., Korhonen, J., Linnanmäki, K., and Aunio, P.. 2020. ‘The Number Race: Computer-Assisted Intervention for Mathematically Low-Performing First Graders’. European Journal of Special Needs Education 35 (1): 85–99.Google Scholar
Helmreich, I., Zuber, J., Pixner, S., et al. 2011. ‘Language Effects on Children’s Nonverbal Number Line Estimations’. Journal of Cross-Cultural Psychology 42 (4): 598–613.Google Scholar
Hensch, T. K. 2004. ‘Critical Period Regulation’. Annual Review of Neuroscience 27 (1): 549–79.Google Scholar
Herbers, J. E., Cutuli, J. J., Supkoff, L. M., et al. 2012. ‘Early Reading Skills and Academic Achievement Trajectories of Students Facing Poverty, Homelessness, and High Residential Mobility’. Educational Researcher 41 (9): 366–74.Google Scholar
Hess, K. 2003. Lehren – zwischen Belehrung und Lernbegleitung: Einstellungen, Umsetzungen und Wirkungen im mathematischen Anfangsunterricht. h.e.p. Verlag.Google Scholar
Heth, I., and Lavidor, M.. 2015. ‘Improved Reading Measures in Adults with Dyslexia Following Transcranial Direct Current Stimulation Treatment’. Neuropsychologia 70 (April): 107–13.Google Scholar
Hibel, J., Farkas, G., and Morgan, P. L.. 2010. ‘Who is Placed into Special Education?’ Sociology of Education 83 (4): 312–32.Google Scholar
Hibel, J., and Jasper, A. D.. 2012. ‘Delayed Special Education Placement for Learning Disabilities Among Children of Immigrants’. Social Forces; a Scientific Medium of Social Study and Interpretation 91 (2): 503–30.Google Scholar
Leiß, D. 2007. ‘“Hilf Mir, Es Selbst Zu Tun”. Lehrerinterventionen Beim Mathematischen Modellieren’. Accessed July 29, 2021. www.fachportal-paedagogik.de/literatur/vollanzeige.html?FId=901385.Google Scholar
Hinshelwood, J. 1900. ‘Congenital Word-Blindness’. The Lancet 155 (4004): 1506–8.Google Scholar
Hirvonen, R., Tolvanen, A., Aunola, K., and Nurmi, J.-E.. 2012. ‘The Developmental Dynamics of Task-Avoidant Behavior and Math Performance in Kindergarten and Elementary School’. Learning and Individual Differences 22 (6): 715–23.Google Scholar
Hjetland, H. N., Brinchmann, E. I., Scherer, R., Hulme, C., and Melby-Lervåg, M.. 2020. ‘Preschool Pathways to Reading Comprehension: A Systematic Meta-Analytic Review’. Educational Research Review 30 (June): 100323.Google Scholar
Ho, C. S.-H., Chan, D. W., Chung, K. K. H., Lee, S.-H., and Tsang, S.-M.. 2007. ‘In Search of Subtypes of Chinese Developmental Dyslexia’. Journal of Experimental Child Psychology 97 (1): 61–83. https://doi.org/10.1016/j.jecp.2007.01.002.Google Scholar
Ho, C. S.-H., and Bryant, P.. 1997. ‘Phonological Skills Are Important in Learning to Read Chinese’. Developmental Psychology 33 (6): 946–51. https://doi.org/10.1037/0012-1649.33.6.946.Google Scholar
Ho, C. S.-H., Chan, D. W.-O., Lee, S.-H., Tsang, S.-M., and Luan, V. H.. 2004. ‘Cognitive Profiling and Preliminary Subtyping in Chinese Developmental Dyslexia’. Cognition 91 (1): 43–75. https://doi.org/10.1016/s0010-0277(03)00163-x.Google Scholar
Ho, C. S.-H., and Fong, K.-M.. 2005. ‘Do Chinese Dyslexic Children Have Difficulties Learning English as a Second Language?’ Journal of Psycholinguistic Research 34: 603–18. https://doi.org/10.1007/s10936-005-9166-1.Google Scholar
Hollingworth, L. S. 1926. Gifted Children: Their Nature and Nurture. Macmillan . https://doi.org/10.1037/10599-000.Google Scholar
Holloway, I. D., and Ansari, D.. 2009. ‘Mapping Numerical Magnitudes onto Symbols: The Numerical Distance Effect and Individual Differences in Children’s Mathematics Achievement’. Journal of Experimental Child Psychology 103 (1): 17–29.Google Scholar
Holm, A., and Dodd, B.. 1996. ‘The Effect of First Written Language on the Acquisition of English Literacy’. Cognition 59 (2): 119–47.Google Scholar
Honig, M. I., ed. 2006. New Directions in Education Policy Implementation: Confronting Complexity. State University of New York Press.Google Scholar
Horwitz, B., Rumsey, J. M., and Donohue, B. C.. 1998. ‘Functional Connectivity of the Angular Gyrus in Normal Reading and Dyslexia’. Proceedings of the National Academy of Sciences 95 (15): 8939–44. https://doi.org/10.1073/pnas.95.15.8939.Google Scholar
Huang, Y.-Z., Lu, M.-K., Antal, A., et al. 2017. ‘Plasticity Induced by Non-Invasive Transcranial Brain Stimulation: A Position Paper’. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology 128 (11): 2318–29.Google Scholar
Huber, C., and Grosche, M.. 2012. ‘Das Response-to-Intervention-Modell Als Grundlage Für Einen Inklusiven Paradigmenwechsel in Der Sonderpädagogik’. Zeitschrift Für Heilpädagogik 63 (8): 312–22.Google Scholar
Huettig, F., Kolinsky, R., and Lachmann, T.. 2018. ‘The Culturally Co-Opted Brain: How Literacy Affects the Human Mind’. Language, Cognition and Neuroscience 33 (3): 275–7. https://doi.org/10.1080/23273798.2018.1425803.Google Scholar
Huettig, F., Lachmann, T., Reis, A., and Petersson, K. M.. 2018. ‘Distinguishing Cause from Effect – Many Deficits Associated with Developmental Dyslexia May Be a Consequence of Reduced and Suboptimal Reading Experience’. Language, Cognition and Neuroscience 33 (3): 333–50. https://doi.org/10.1080/23273798.2017.1348528.Google Scholar
Hughes, J. A., Phillips, G., and Reed, P.. 2013. ‘Brief Exposure to a Self-Paced Computer-Based Reading Programme and How It Impacts Reading Ability and Behaviour Problems’. PloS One 8 (11): e77867.Google Scholar
Hull, C., and Hjern, B.. 1982. ‘Helping Small Firms Grow: An Implementation Analysis of Small Firm Assistance Structures’. European Journal of Political Research 10 (2): 187–98.Google Scholar
Hulme, C., Goetz, K., Gooch, D., Adams, J., and Snowling, M. J.. 2007. ‘Paired-Associate Learning, Phoneme Awareness, and Learning to Read’. Journal of Experimental Child Psychology 96 (2): 150–66.Google Scholar
Hulme, Charles, Hatcher, Peter J., Nation, Kate, et al. 2002. ‘Phoneme Awareness Is a Better Predictor of Early Reading Skill than Onset-Rime Awareness’. Journal of Experimental Child Psychology 82 (1): 2–28.Google Scholar
Hulme, C., and Snowling, M. J.. 2013. Developmental Disorders of Language Learning and Cognition. John Wiley & Sons.Google Scholar
Hulme, C., and Snowling, M. J. 2015. ‘Learning to Read: What We Know and What We Need to Understand Better’. Child Development Perspectives 7 (1): 1–5.Google Scholar
Hulme, C., Muter, V. V., and Snowling, M.. 1998. ‘Segmentation Does Predict Early Progress in Learning to Read Better than Rhyme: A Reply to Bryant’. Journal of Experimental Child Psychology 71 (1): 39–44.CrossRefGoogle ScholarPubMed
Hung, Y.-H., Frost, S. J., and Pugh, K. R.. 2018. ‘Domain Generality and Specificity of Statistical Learning and Its Relation with Reading Ability’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 33–55. Springer International Publishing.Google Scholar
Hurwitz, S., Perry, B., Cohen, E. D., and Skiba, R.. 2020. ‘Special Education and Individualized Academic Growth: A Longitudinal Assessment of Outcomes for Students With Disabilities’. American Educational Research Journal 57 (2): 576–611.Google Scholar
Hutchison, J. E., Lyons, I. M., and Ansari, D.. 2019. ‘More Similar Than Different: Gender Differences in Children’s Basic Numerical Skills Are the Exception Not the Rule’. Child Development 90 (1): e66–79.Google Scholar
Hu, W., Lee, H. L., Zhang, Q., et al. 2010. ‘Developmental Dyslexia in Chinese and English Populations: Dissociating the Effect of Dyslexia from Language Differences’. Brain: A Journal of Neurology 133 (Pt 6): 1694–706.Google Scholar
Hyde, D. C., and Spelke, E. S.. 2012. ‘Spatiotemporal Dynamics of Processing Nonsymbolic Number: An Event-Related Potential Source Localization Study’. Human Brain Mapping 33 (9): 2189–203.Google Scholar
Hyde, J. S. 2005. ‘The Gender Similarities Hypothesis’. The American Psychologist 60 (6): 581–92.Google Scholar
Hyde, J. S., and McKinley, N. M.. 1997. ‘Gender Differences in Cognition’. In Gender Differences in Human Cognition, Oxford Scholarship Online. https://doi.org/10.1093/acprof:oso/9780195112917.003.0002.Google Scholar
Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., and Williams, C. C.. 2008. ‘Diversity. Gender Similarities Characterize Math Performance’. Science 321 (5888): 494–5.Google Scholar
Hyde, J. S., and Linn, M. C.. 1988. ‘Gender Differences in Verbal Ability: A Meta-Analysis’. Psychological Bulletin 104 (1): 53.Google Scholar
‘ICD-10 Version:2019’. n.d. Accessed June 10, 2021. https://icd.who.int/browse10/2019/en.Google Scholar
‘ICD-11’. n.d. Accessed July 29, 2021. https://icd.who.int/.Google Scholar
Imbo, I., Bulcke, C. V., De Brauwer, J., and Fias, W.. 2014. ‘Sixty-Four or Four-and-Sixty? The Influence of Language and Working Memory on Children’s Number Transcoding’. Frontiers in Psychology 5 (April): 313.Google Scholar
‘Individuelle Lernunterstützung in Schülerarbeitsphasen. Eine Videobasierte Analyse Des Unterstützungsverhaltens von Lehrpersonen Im Mathematikunterricht’. n.d. Accessed July 29, 2021. https://www.fachportal-paedagogik.de/literatur/vollanzeige.html?FId=880554.Google Scholar
Ingram, H. A. P. 1978. ‘Soil Layers in Mires: Function and Terminology’. Journal of Soil Science 29 (2): 224–7.Google Scholar
Ise, E., and Schulte-Körne, G.. 2013. ‘Symptomatik, Diagnostik Und Behandlung Der Rechenstörung’. Zeitschrift Für Kinder- Und Jugendpsychiatrie Und Psychotherapie 41 (4): 271–82. https://doi.org/10.1024/1422-4917/a000241.Google Scholar
Iuculano, T., and Cohen Kadosh, R. 2014. ‘Preliminary Evidence for Performance Enhancement Following Parietal Lobe Stimulation in Developmental Dyscalculia’. Frontiers in Human Neuroscience 8 (February): 38.Google Scholar
Jacobson, L., Koslowsky, M., and Lavidor, M.. 2012. ‘tDCS Polarity Effects in Motor and Cognitive Domains: A Meta-Analytical Review’. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale 216 (1): 1–10.Google Scholar
James, W. H. 2000. ‘Why Are Boys More Likely to Be Preterm than Girls? Plus Other Related Conundrums in Human Reproduction’. Human Reproduction 15 (10): 2108–11.Google Scholar
Jamison, Eliot A., Jamison, Dean T., and Hanushek, Eric A.. 2007. ‘The Effects of Education Quality on Income Growth and Mortality Decline’. Economics of Education Review 26 (6): 771–88.Google Scholar
Jiménez, J. E., de la Cadena, C. G., Siegel, L. S., et al. 2011. ‘Gender Ratio and Cognitive Profiles in Dyslexia: A Cross-National Study’. Reading and Writing 24 (7): 729–47.Google Scholar
Jimenez, J. E., del Rosario Ortiz, M., Rodrigo, M., et al. 2003. ‘Do the Effects of Computer-Assisted Practice Differ for Children with Reading Disabilities With and Without IQ – Achievement Discrepancy?’ Journal of Learning Disabilities 36 (1): 34–47.Google Scholar
Jirout, J. J., and Newcombe, N. S.. 2015. ‘Building Blocks for Developing Spatial Skills: Evidence from a Large, Representative US Sample’. Psychological Science 26 (3): 302–10.Google Scholar
Joel, D., and Fausto-Sterling, A.. 2016. ‘Beyond Sex Differences: New Approaches for Thinking about Variation in Brain Structure and Function’. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 371 (1688): 20150451.Google Scholar
Johnson, E., Mellard, D. F., Fuchs, D., and McKnight, M. A.. 2006. ‘Responsiveness to Intervention (RTI): How to Do It. [RTI Manual]’. National Research Center on Learning Disabilities, August. http://files.eric.ed.gov/fulltext/ED496979.pdf.Google Scholar
Jones, M. G., and Wheatley, J.. 1990. ‘Gender Differences in Teacher-Student Interactions in Science Classrooms’. Journal of Research in Science Teaching 27 (9): 861–74. https://doi.org/10.1002/tea.3660270906.Google Scholar
Jong, P. F. de, and van Bergen, E.. 2017. Issues in Diagnosing Dyslexia. John Benjamins Publishing Company. https://benjamins.com/catalog/z.206.21dej.Google Scholar
Jordan, N. C., Huttenlocher, J., and Levine, S. C.. 1992. ‘Differential Calculation Abilities in Young Children from Middle- and Low-Income Families’. Developmental Psychology 28 (4): 644–53. https://doi.org/10.1037/0012-1649.28.4.644.Google Scholar
Jordan, N. C., Kaplan, D, Locuniak, M. N., and Ramineni, C.. 2007. ‘Predicting First-Grade Math Achievement from Developmental Number Sense Trajectories’. Learning Disabilities Research & Practice 22 (1): 36–46. https://doi.org/10.1111/j.1540-5826.2007.00229.x.Google Scholar
Jordan, N. C., Kaplan, D., Ramineni, C., and Locuniak, M. N.. 2009a. ‘Early Math Matters: Kindergarten Number Competence and Later Mathematics Outcomes’. Developmental Psychology 45 (3): 850–67. https://doi.org/10.1037/a0014939.Google Scholar
Jordan, N. C., Kaplan, D., Ramineni, C., and Locuniak, M. N. 2009b. ‘Early Math Matters: Kindergarten Number Competence and Later Mathematics Outcomes’. Developmental Psychology 45 (3): 850–67.Google Scholar
Joshi, R. M. 2018. ‘Simple View of Reading (SVR) in Different Orthographies: Seeing the Forest with the Trees’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 71–80. Springer International Publishing.Google Scholar
Joshi, R. M., and Wijekumar, K.. 2020. ‘Introduction to the Special Issue: “Teacher Knowledge of Literacy Skills.”’ Dyslexia 26 (2): 117–19.Google Scholar
Josselyn, S. A., and Frankland, P. W.. 2012. ‘Infantile Amnesia: A Neurogenic Hypothesis’. Learning & Memory 19 (9): 423–33.Google Scholar
Jovanović, G., Jovanović, Z., Banković-Gajić, J., et al. 2013. ‘The Frequency of Dyscalculia among Primary School Children’. Psychiatria Danubina 25 (2): 170–74.Google Scholar
Joyce, T., and Borgwaldt, S. R.. 2013. ‘Typology of Writing Systems’. Typology of Writing Systems 51: 1–12. https://doi.org/10.1075/bct.51.01joy.Google Scholar
Józsa, K., and Caplovitz Barrett, K. 2018. ‘Affective and Social Mastery Motivation in Preschool as Predictors of Early School Success: A Longitudinal Study’. Early Childhood Research Quarterly 45 (October): 81–92.Google Scholar
Jussim, L., and Eccles, J. S.. 1992. ‘Teacher Expectations: II. Construction and Reflection of Student Achievement’. Journal of Personality and Social Psychology 63 (6): 947–61. https://doi.org/10.1037/0022-3514.63.6.947.Google Scholar
Kang, C. Y., Duncan, G. J., Clements, D. H., Sarama, J., and Bailey, D. H.. 2019. ‘The Roles of Transfer of Learning and Forgetting in the Persistence and Fadeout of Early Childhood Mathematics Interventions’. Journal of Educational Psychology 111 (4): 590–603.Google Scholar
Karbach, J., Strobach, T., and Schubert, T.. 2015. ‘Adaptive Working-Memory Training Benefits Reading, but Not Mathematics in Middle Childhood’. Child Neuropsychology: A Journal on Normal and Abnormal Development in Childhood and Adolescence 21 (3): 285–301.Google Scholar
Karlsen, J., Halaas Lyster, S.-A, and Lervåg, A.. 2017. ‘Vocabulary Development in Norwegian L1 and L2 Learners in the Kindergarten-School Transition’. Journal of Child Language 44 (2): 402–26.Google Scholar
Kaufmann, L., Handl, P., and Thöny, B.. 2003. ‘Evaluation of a Numeracy Intervention Program Focusing on Basic Numerical Knowledge and Conceptual Knowledge: A Pilot Study’. Journal of Learning Disabilities 36 (6): 564–73.Google Scholar
Kaufmann, L., Nuerk, H. C., Graf, M., Krinzinger, H., Delazer, M., and Willmes, K.. 2009. ‘TEDI-MATH: Test Zur Erfassung Numerisch-Rechnerischer Fertigkeiten Für 4-8 Jährige’. https://uni-salzburg.elsevierpure.com/en/publications/tedi-math-test-zur-erfassung-numerisch-rechnerischer-fertigkeiten.Google Scholar
Kaufmann, L., and Pixner, S.. 2012. ‘New Approaches to Teaching Early Number Skills and to Remediate Number Fact Dyscalculia’. In Reading, Writing, Mathematics and the Developing Brain: Listening to Many Voices, edited by Breznitz, Z., Rubinsten, O., Molfese, V. J., and Molfese, D. L., 277–94. Springer Netherlands.Google Scholar
Kay, J., and Yeo, D.. 2012. Dyslexia and Maths. David Fulton Publishers. https://doi.org/10.4324/9780203459478.Google Scholar
Kekic, M., Boysen, E, Campbell, I. C, and Schmidt, U. 2016. ‘A Systematic Review of the Clinical Efficacy of Transcranial Direct Current Stimulation (tDCS) in Psychiatric Disorders’. Journal of Psychiatric Research 74 (March): 70–86.Google Scholar
Keller, K., and Menon, V.. 2009. ‘Gender Differences in the Functional and Structural Neuroanatomy of Mathematical Cognition’. NeuroImage 47 (1): 342–52.Google Scholar
Kelly, Steven N. 1998. ‘Preschool Classroom Teachers’ Perceptions of Useful Music Skills and Understandings’. Journal of Research in Music Education 46 (3): 374–83. https://doi.org/10.2307/3345549.Google Scholar
Kennedy, N. I., Lee, W. H., and Frangou, S.. 2018. ‘Efficacy of Non-Invasive Brain Stimulation on the Symptom Dimensions of Schizophrenia: A Meta-Analysis of Randomized Controlled Trials’. European Psychiatry: The Journal of the Association of European Psychiatrists 49 (March): 69–77.Google Scholar
Keong, W. K., Pang, V., Eng, C. K., and Keong, T. C.. 2016. ‘Prevalence Rate of Dyscalculia According to Gender and School Location in Sabah, Malaysia’. In 7th International Conference on University Learning and Teaching (InCULT 2014) Proceedings, 91–100. Springer Singapore.Google Scholar
Kersey, A. J., Braham, E. J., Csumitta, K. D., Libertus, M. E., and Cantlon, J. F.. 2018. ‘No Intrinsic Gender Differences in Children’s Earliest Numerical Abilities’. NPJ Science of Learning 3 (July): 12.Google Scholar
Kersey, A. J., Csumitta, K. D., and Cantlon, J. F.. 2019. ‘Gender Similarities in the Brain during Mathematics Development’. NPJ Science of Learning 4 (November): 19.Google Scholar
Kershner, J. R. 2019. ‘Neurobiological Systems in Dyslexia’. Trends in Neuroscience and Education 14 (March): 11–24.Google Scholar
Khong, L. Y.-L., and Ng, P. T.. 2005. ‘School–Parent Partnerships in Singapore’. Educational Research for Policy and Practice 4: 1–11. https://doi.org/10.1007/s10671-005-5617-6.Google Scholar
Kiger, D., Herro, D., and Prunty, D.. 2012. ‘Examining the Influence of a Mobile Learning Intervention on Third Grade Math Achievement’. International Journal of Information and Communication Technology Education: An Official Publication of the Information Resources Management Association 45 (1): 61–82.Google Scholar
Kim, S. Y., Liu, L., and Cao, F.. 2017. ‘How Does First Language (L1) Influence Second Language (L2) Reading in the Brain? Evidence from Korean-English and Chinese-English Bilinguals’. Brain and Language 171 (August): 1–13.Google Scholar
Kim, S. Y., Qi, T., Feng, X., Ding, G., Liu, L., and Cao, Fan. 2016. ‘How Does Language Distance between L1 and L2 Affect the L2 Brain Network? An fMRI Study of Korean–Chinese–English Trilinguals’. NeuroImage 129: 25–39. https://doi.org/10.1016/j.neuroimage.2015.11.068.Google Scholar
Kirschner, P. A., Sweller, J., and Clark, R. E.. 2006. ‘Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching’. Educational Psychologist 41 (2): 75–86.Google Scholar
Kita, Y., Yamamoto, H., Oba, K., et al. 2013. ‘Altered Brain Activity for Phonological Manipulation in Dyslexic Japanese Children’. Brain: A Journal of Neurology 136 (Pt 12): 3696–708.Google Scholar
Kivirauma, J., and Ruoho, K.. 2007. ‘Excellence through Special Education? Lessons from the Finnish School Reform’. International Review of Education. Internationale Zeitschrift Fur Erziehungswissenschaft. Revue Internationale de Pedagogie 53 (3): 283–302.Google Scholar
Kjeldsen, A.-C., Niemi, P., and Olofsson, Å. 2003. ‘Training Phonological Awareness in Kindergarten Level Children: Consistency Is More Important than Quantity’. Learning and Instruction 13 (4): 349–65. https://doi.org/10.1016/s0959-4752(02)00009-9.Google Scholar
Kjeldsen, A.-C., Educ, L., Saarento-Zaprudin, S. K., and Niemi, P. O.. 2019. ‘Kindergarten Training in Phonological Awareness: Fluency and Comprehension Gains Are Greatest for Readers at Risk in Grades 1 Through 9’. Journal of Learning Disabilities 52 (5): 366–82. https://doi.org/10.1177/0022219419847154.Google Scholar
Kjeldsen, A.-C., Kärnä, A., Niemi, P., Olofsson, Å, and Witting, K.. 2014. ‘Gains From Training in Phonological Awareness in Kindergarten Predict Reading Comprehension in Grade 9’. Scientific Studies of Reading 18 (6): 452–67. https://doi.org/10.1080/10888438.2014.940080.Google Scholar
Klatte, M., Bergström, K., Steinbrink, C., Konerding, M., and Lachmann, T.. 2018. ‘Effects of the Computer-Based Training Program Lautarium on Phonological Awareness and Reading and Spelling Abilities in German Second-Graders’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 323–39. Springer International Publishing.Google Scholar
Klatte, M., Spilski, J., Mayerl, J., et al. 2017. ‘Effects of Aircraft Noise on Reading and Quality of Life in Primary School Children in Germany: Results From the NORAH Study’. Environment and Behavior 49 (4): 390–424.Google Scholar
Kleemans, T., Peeters, M., Segers, E., and Verhoeven, L.. 2012. ‘Child and Home Predictors of Early Numeracy Skills in Kindergarten’. Early Childhood Research Quarterly 27 (3): 471–7.Google Scholar
Klein, E., Suchan, J., Moeller, K., et al. 2016. ‘Considering Structural Connectivity in the Triple Code Model of Numerical Cognition: Differential Connectivity for Magnitude Processing and Arithmetic Facts’. Brain Structure & Function 221 (2): 979–95.Google Scholar
Klibanoff, R. S., Levine, S. C., Huttenlocher, J., Vasilyeva, M., and Hedges, L. V.. 2006. ‘Preschool Children’s Mathematical Knowledge: The Effect of Teacher “Math Talk.”’ Developmental Psychology 42 (1): 59–69.Google Scholar
Klingner, J. K. 2006. ‘The Special Education Referral and Decision-Making Process for English Language Learners: Child Study Team Meetings and Staffing,’ May. https://nepc.colorado.edu/publication/special-education-referral-and-decision-making-process-english-language-learners-child-s.Google Scholar
Klock, H. 2020. Adaptive Interventionskompetenz in Mathematischen Modellierungsprozessen: Konzeptualisierung, Operationalisierung und Förderung. 1st ed. Studien Zur Theoretischen Und Empirischen Forschung In der M. Springer Spektrum.Google Scholar
Koeda, T., Seki, A., Uchiyama, H., and Sadato, N.. 2011. ‘Dyslexia: Advances in Clinical and Imaging Studies’. Brain & Development 33 (3): 268–75.Google Scholar
Kohn, J., Rauscher, L., Kucian, K., et al. 2020. ‘Efficacy of a Computer-Based Learning Program in Children With Developmental Dyscalculia. What Influences Individual Responsiveness?’ Frontiers in Psychology 11 (July): 1115.Google Scholar
Kolinsky, R., Gabriel, R., Demoulin, C., et al. 2020. ‘The Influence of Age, Schooling, Literacy, and Socioeconomic Status on Serial-Order Memory’. Journal of Cultural Cognitive Science 4 (3): 343–65.Google Scholar
Kollosche, D., Marcone, R., Knigge, M., et al., eds. 2019. Inclusive Mathematics Education: State-of-the-Art Research from Brazil and Germany. 1st ed. Springer Nature.Google Scholar
Konerding, M., Bergström, K., Lachmann, T., and Klatte, M.. 2020. ‘Effects of Computerized Grapho-Phonological Training on Literacy Acquisition and Vocabulary Knowledge in Children with an Immigrant Background Learning German as L2’. Journal of Cultural Cognitive Science 4: 367–83. https://doi.org/10.1007/s41809-020-00064-3.Google Scholar
Kong, A., Thorleifsson, G., Frigge, M. L., et al. 2018. ‘The Nature of Nurture: Effects of Parental Genotypes’. Science 359 (6374): 424–8.Google Scholar
Koponen, T., Aro, M., Poikkeus, A.-M., et al. 2018. ‘Comorbid Fluency Difficulties in Reading and Math: Longitudinal Stability Across Early Grades’. Exceptional Children 84 (3): 298–311.Google Scholar
Koponen, T., Aunola, K., Ahonen, T., and Nurmi, J.-E.. 2007. ‘Cognitive Predictors of Single-Digit and Procedural Calculation Skills and Their Covariation with Reading Skill’. Journal of Experimental Child Psychology 97 (3): 220–41.Google Scholar
Korucu, I., Rolan, E., Napoli, A. R., Purpura, D. J., and Schmitt, S. A.. 2019. ‘Development of the Home Executive Function Environment (HEFE) Scale: Assessing Its Relation to Preschoolers’ Executive Function’. Early Childhood Research Quarterly 47 (April): 9–19.Google Scholar
Kosc, L. 1974. ‘Developmental Dyscalculia’. Journal of Learning Disabilities 7 (3): 164–77.Google Scholar
Koshmider, J. W., and Ashcraft, M. H.. 1991. ‘The Development of Children’s Mental Multiplication Skills’. Journal of Experimental Child Psychology 51 (1): 53–89.Google Scholar
Koumoula, A., Tsironi, V., Stamouli, V., et al. 2004. ‘An Epidemiological Study of Number Processing and Mental Calculation in Greek Schoolchildren’. Journal of Learning Disabilities 37 (5): 377–88.Google Scholar
Kovas, Y., Voronin, I., Kaydalov, A, Malykh, S. B., Dale, P. S., and Plomin, R.. 2013. ‘Literacy and Numeracy Are More Heritable Than Intelligence in Primary School’. Psychological Science 24 (10): 2048–56.Google Scholar
Koyama, M. S., Hansen, P. C., and Stein, J. F.. 2008. ‘Logographic Kanji versus Phonographic Kana in Literacy Acquisition’. Annals of the New York Academy of Sciences 1145 (1): 41–55. https://doi.org/10.1196/annals.1416.005.Google Scholar
Krajewski, K., Nieding, G., and Schneider, W.. 2008. ‘Kurz- Und Langfristige Effekte Mathematischer Frühförderung Im Kindergarten Durch Das Programm “Mengen, Zählen, Zahlen”’. Zeitschrift Für Entwicklungspsychologie Und Pädagogische Psychologie 40 (3): 135–46. https://doi.org/10.1026/0049-8637.40.3.135.Google Scholar
Krajewski, K., and Schneider, W.. 2009a. ‘Early Development of Quantity to Number-Word Linkage as a Precursor of Mathematical School Achievement and Mathematical Difficulties: Findings from a Four-Year Longitudinal Study’. Learning and Instruction 19 (6): 513–26. https://doi.org/10.1016/j.learninstruc.2008.10.002.Google Scholar
Krajewski, K., and Schneider, W. 2009b. ‘Exploring the Impact of Phonological Awareness, Visual–spatial Working Memory, and Preschool Quantity–number Competencies on Mathematics Achievement in Elementary School: Findings from a 3-Year Longitudinal Study’. Journal of Experimental Child Psychology 103 (4): 516–31. https://doi.org/10.1016/j.jecp.2009.03.009.Google Scholar
Kramarski, B., Mevarech, Z. R., and Arami, M.. 2002. ‘The Effects of Metacognitive Instruction on Solving Mathematical Authentic Tasks’. Educational Studies in Mathematics 49 (2): 225–50.Google Scholar
Krapohl, E., and Plomin, R.. 2015. ‘Genetic Link between Family Socioeconomic Status and Children’s Educational Achievement Estimated from Genome-Wide SNPs’. Molecular Psychiatry 21 (3): 437–43.Google Scholar
Krause, B., and Cohen Kadosh, R.. 2014. ‘Not All Brains Are Created Equal: The Relevance of Individual Differences in Responsiveness to Transcranial Electrical Stimulation’. Frontiers in Systems Neuroscience 8 (February): 25.Google Scholar
Kroeger, L., and Brown, R. D.. 2018. ‘Enhancing Mathematical Cognitive Development Through Educational Interventions’. In Neuroscience of Mathematical Cognitive Development: From Infancy Through Emerging Adulthood, edited by Douglas Brown, R, 119–36. Springer International Publishing.Google Scholar
Kroesbergen, E. H., and van Luit, J. E. H. 2002. ‘Teaching Multiplication to Low Math Performers: Guided versus Structured Instruction’. Instructional Science 30 (5): 361–78.Google Scholar
Kroesbergen, E. H., and van Luit, J. E. H.. 2003. ‘Mathematics Interventions for Children with Special Educational Needs’. Remedial and Special Education: RASE 24 (2): 97–114.Google Scholar
Krull, J., Wilbert, J., and Hennemann, T.. 2014. ‘The Social and Emotional Situation of First Graders with Classroom Behavior Problems and Classroom Learning Difficulties in Inclusive Classes’. Learning Disabilities–A Contemporary Journal 12 (2). www.researchgate.net/profile/Juergen_Wilbert2/publication/269391716_The_Social_and_Emotional_Situation_of_First_Graders_with_Classroom_Behavior_Problems_and_Classroom_Learning_Difficulties_in_Inclusive_Classes/links/5488407d0cf268d28f08b9c5.pdf.Google Scholar
Kucian, K., and von Aster, M.. 2015. ‘Developmental Dyscalculia’. European Journal of Pediatrics 174 (1): 1–13.Google Scholar
Kuhn, J.-T., and Holling, H.. 2014. ‘Number Sense or Working Memory? The Effect of Two Computer-Based Trainings on Mathematical Skills in Elementary School’. Advances in Cognitive Psychology / University of Finance and Management in Warsaw 10 (2): 59–67.Google Scholar
Lachmann, T. 2002. ‘Reading Disability as a Deficit in Functional Coordination’. In Basic Functions of Language, Reading and Reading Disability, edited by Witruk, E., Friederici, A. D., and Lachmann, T., 165–98. Springer US.Google Scholar
Lachmann, T. 2008. ‘Experimental Approaches to Specific Disabilities in Learning to Read: The Case of Symmetry Generalization in Developmental Dyslexia’. In Srinivasan, N, Gupta, A. K, and Pandey, J. (eds.), Advances in Cognitive Science, 321–42. Sage Publications.Google Scholar
Lachmann, T 2018. ‘Reading and Dyslexia: The Functional Coordination Framework’. In Reading and Dyslexia: From Basic Functions to Higher Order Cognition, edited by Lachmann, T. and Weis, T., 271–96. Springer International Publishing.Google Scholar
Lachmann, T., Berti, S., Kujala, T., and Schröger, E.. 2005. ‘Diagnostic Subgroups of Developmental Dyslexia Have Different Deficits in Neural Processing of Tones and Phonemes’. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology 56 (2): 105–20.Google Scholar
Lachmann, T., and van Leeuwen, C.. 2014. ‘Reading as Functional Coordination: Not Recycling but a Novel Synthesis’. Frontiers in Psychology 5 (September): 1046.Google Scholar
Lachmann, T., and Van Leeuwen, C.. 2008. ‘Different Letter-Processing Strategies in Diagnostic Subgroups of Developmental Dyslexia’. Cognitive Neuropsychology 25 (5): 730–44. https://doi.org/10.1080/02643290802309514.Google Scholar
Lachmann, T., and Weis, T.. 2018. Reading and Dyslexia: From Basic Functions to Higher Order Cognition. Springer International Publishing.Google Scholar
Lambert, K., and Spinath, B.. 2014. ‘Do We Need a Special Intervention Program for Children with Mathematical Learning Disabilities or Is Private Tutoring Sufficient?’ Waxmann. https://doi.org/10.25656/01:8841/ https://nbn-resolving.org/urn:nbn:de:0111-opus-88416.Google Scholar
Lambert, K., and Spinath, B. 2018. ‘Are WISC IQ Scores in Children with Mathematical Learning Disabilities Underestimated? The Influence of a Specialized Intervention on Test Performance’. Research in Developmental Disabilities 72: 56–66. https://doi.org/10.1016/j.ridd.2017.10.016.Google Scholar
Landerl, K., Freudenthaler, H. H., Heene, M., et al. 2019. ‘Phonological Awareness and Rapid Automatized Naming as Longitudinal Predictors of Reading in Five Alphabetic Orthographies with Varying Degrees of Consistency’. Scientific Studies of Reading 23 (3): 230–4. https://doi.org/10.1080/10888438.2018.1510936.Google Scholar
Landerl, K., and Wimmer, H.. 2008. ‘Development of Word Reading Fluency and Spelling in a Consistent Orthography: An 8-Year Follow-Up’. Journal of Educational Psychology 100 (1): 150–61. https://doi.org/10.1037/0022-0663.100.1.150.Google Scholar
Landerl, K., Wimmer, H., and Frith, U.. 1997. ‘The Impact of Orthographic Consistency on Dyslexia: A German-English Comparison’. Cognition 63 (3): 315–34.Google Scholar
Laycock, R., Crewther, D. P., Fitzgerald, P. B., and Crewther, S. G.. 2009. ‘TMS Disruption of V5/MT+ Indicates a Role for the Dorsal Stream in Word Recognition’. Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale 197 (1): 69–79.Google Scholar
Layes, S., Lalonde, R., Bouakkaz, Y., and Rebai, M.. 2018. ‘Effectiveness of Working Memory Training among Children with Dyscalculia: Evidence for Transfer Effects on Mathematical Achievement-a Pilot Study’. Cognitive Processing 19 (3): 375–85.Google Scholar
Lazonder, A. W., and Harmsen, R.. 2016. ‘Meta-Analysis of Inquiry-Based Learning’. Review of Educational Research 86 (3): 681–718.Google Scholar
Lazzaro, G., Costanzo, F., Varuzza, C., et al. 2020. ‘Individual Differences Modulate the Effects of tDCS on Reading in Children and Adolescents with Dyslexia’. Scientific Studies of Reading 25 (6): 470–85. https://doi.org/10.1080/10888438.2020.1842413.Google Scholar
Leahy, A. M. 1961. ‘Nature-Nurture and Intelligence’. In Jenkins, J. and Paterson, D. G (Eds.),Studies in Individual Differences: The Search for Intelligence, pp. 376–95. https://doi.org/10.1037/11491-031.Google Scholar
Le Corre, M., and Carey, S.. 2007. ‘One, Two, Three, Four, Nothing More: An Investigation of the Conceptual Sources of the Verbal Counting Principles’. Cognition 105 (2): 395–438.Google Scholar
Lee, K.-M. 2004. ‘Functional MRI Comparison between Reading Ideographic and Phonographic Scripts of One Language’. Brain and Language 91 (2): 245–51.Google Scholar
Lee Swanson, H., and Sachse-Lee, C.. 2000. ‘A Meta-Analysis of Single-Subject-Design Intervention Research for Students with LD’. Journal of Learning Disabilities 33 (2): 114–36.Google Scholar
Lefevre, J.-A., Lira, C. J., Sowinski, C., et al. 2013. ‘Charting the Role of the Number Line in Mathematical Development’. Frontiers in Psychology 4 (September): 641.Google Scholar
LeFevre, J.-A., Skwarchuk, S.-L., Smith-Chant, B. L., et al. 2009. ‘Home Numeracy Experiences and Children’s Math Performance in the Early School Years’. Canadian Journal of Behavioural Science. Revue Canadienne Des Sciences Du Comportement 41 (2): 55–66.Google Scholar
Lekgoko, O., and Winskel, H.. 2008. ‘Learning to Read Setswana and English: Cross-Language Transference of Letter Knowledge, Phonological Awareness and Word Reading Skills’. Perspectives in Education 26 (4): 57–73.Google Scholar
Lê, M.-L. T., and Noël, M.-P.. 2020. ‘Transparent Number-Naming System Gives Only Limited Advantage for Preschooler’s Numerical Development: Comparisons of Vietnamese and French-Speaking Children’. PloS One 15 (12): e0243472.Google Scholar
Lenhard, A., Lenhard, W., Schug, M., and Kowalski, A.. 2011. ‘Computerbasierte Mathematikförderung Mit Den “Rechenspielen Mit Elfe Und Mathis I”’. Zeitschrift Für Entwicklungspsychologie Und Pädagogische Psychologie 43 (2): 79–88. https://doi.org/10.1026/0049-8637/a000037.Google Scholar
Leonard, B. D., and Conrad, P.. 1978. ‘Identifying Hyperactive Children: The Medicalization of Deviant Behavior’. Contemporary Sociology 7 (6): 746–7. https://doi.org/10.2307/2065693.Google Scholar
Lervåg, A. 2005. Prediction of Development in Beginning Reading and Spelling: A Norwegian Latent Variable Study. Unipub, Univ. of Oslo, Fac. of Education.Google Scholar
Lervåg, A 2020. ‘Editorial: Some Roads Less Travelled-Different Routes to Understanding the Causes of Child Psychopathology’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 61 (6): 625–7.Google Scholar
Lervåg, A., and Aukrust, V. G.. 2010. ‘Vocabulary Knowledge Is a Critical Determinant of the Difference in Reading Comprehension Growth between First and Second Language Learners’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 51 (5): 612–20.Google Scholar
Lervåg, A., Bråten, I., and Hulme, C.. 2009. ‘The Cognitive and Linguistic Foundations of Early Reading Development: A Norwegian Latent Variable Longitudinal Study’. Developmental Psychology 45 (3): 764–81.Google Scholar
Lervåg, A., and Hulme, C.. 2009. ‘Rapid Automatized Naming (RAN) Taps a Mechanism That Places Constraints on the Development of Early Reading Fluency’. Psychological Science 20 (8): 1040–8.Google Scholar
Leung, F. K. S. 2014. ‘What Can and Should We Learn from International Studies of Mathematics Achievement?’ Mathematics Education Research Journal 26 (3): 579–605.Google Scholar
Levine, S. C., Huttenlocher, J., Taylor, A., and Langrock, A.. 1999. ‘Early Sex Differences in Spatial Skill’. Developmental Psychology 35 (4): 940–9. https://doi.org/10.1037/0012-1649.35.4.940.Google Scholar
Levine, S. C., Ratliff, K. R., Huttenlocher, J., and Cannon, J.. 2012. ‘Early Puzzle Play: A Predictor of Preschoolers’ Spatial Transformation Skill’. Developmental Psychology 48 (2): 530–42.Google Scholar
Levine, S. C., Suriyakham, L. W., Rowe, M. L., Huttenlocher, J., and Gunderson, E. A.. 2010. ‘What Counts in the Development of Young Children’s Number Knowledge?’ Developmental Psychology 46 (5): 1309–19.Google Scholar
Lewis, C., Hitch, G. J., and Walker, P.. 1994. ‘The Prevalence of Specific Arithmetic Difficulties and Specific Reading Difficulties in 9- to 10-Year-Old Boys and Girls’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 35 (2): 283–92.Google Scholar
Libertus, M. E., Feigenson, L., and Halberda, J.. 2013. ‘Is Approximate Number Precision a Stable Predictor of Math Ability?’ Learning and Individual Differences 25 (June): 126–33.Google Scholar
Libertus, M. E., Odic, D., Feigenson, L., and Halberda, J.. 2016. ‘The Precision of Mapping between Number Words and the Approximate Number System Predicts Children’s Formal Math Abilities’. Journal of Experimental Child Psychology 150 (October): 207–26.Google Scholar
Liederman, J., Kantrowitz, L., and Flannery, K.. 2005. ‘Male Vulnerability to Reading Disability Is Not Likely to Be a Myth: A Call for New Data’. Journal of Learning Disabilities 38 (2): 109–29.Google Scholar
Lindberg, S. M., Shibley Hyde, J., Petersen, J. L., and Linn, M. C.. 2010. ‘New Trends in Gender and Mathematics Performance: A Meta-Analysis’. Psychological Bulletin 136 (6): 1123–35.Google Scholar
Lin, Y., Zhang, X., Huang, Q, et al. 2020. ‘The Prevalence of Dyslexia in Primary School Children and Their Chinese Literacy Assessment in Shantou, China’. International Journal of Environmental Research and Public Health 17 (19). https://doi.org/10.3390/ijerph17197140.Google Scholar
Lipsky, M. 1971. ‘Street-Level Bureaucracy and the Analysis of Urban Reform’. Urban Affairs Quarterly 6 (4): 391–409.Google Scholar
Little, T. D. 2013. Longitudinal Structural Equation Modeling. Guilford Press.Google Scholar
Liu, K.-Y., King, M., and Bearman, P. S.. 2010. ‘Social Influence and the Autism Epidemic’. AJS; American Journal of Sociology 115 (5): 1387–434.Google Scholar
Liu, L., Tao, R., Wang, W., et al. 2013. ‘Chinese Dyslexics Show Neural Differences in Morphological Processing’. Developmental Cognitive Neuroscience 6: 40–50. https://doi.org/10.1016/j.dcn.2013.06.004.Google Scholar
Liu, P. D., Mcbride-Chang, C., Wong, T. T.-Y., Shu, H., and Wong, A. M.-Y.. 2013. ‘Morphological Awareness in Chinese: Unique Associations of Homophone Awareness and Lexical Compounding to Word Reading and Vocabulary Knowledge in Chinese Children’. Applied Psycholinguistics 34 (4): 755–75. https://doi.org/10.1017/s014271641200001x.Google Scholar
Lloyd, J. W., Kauffman, J. M., Landrum, T.J., and Roe, D. L.. 1991. ‘Why Do Teachers Refer Pupils for Special Education? An Analysis of Referral Records’. Exceptionality 2 (3): 115–26.Google Scholar
Logan, S., and Johnston, R.. 2009. ‘Gender Differences in Reading Ability and Attitudes: Examining Where These Differences Lie’. Journal of Research in Reading 32 (2): 199–214.Google Scholar
Logan, S., and Johnston, R. 2010. ‘Investigating Gender Differences in Reading’. Educational Review 62 (2): 175–87.Google Scholar
Logan, S., and Medford, E.. 2011. ‘Gender Differences in the Strength of Association between Motivation, Competency Beliefs and Reading Skill’. Educational Research 53 (1): 85–94. https://doi.org/10.1080/00131881.2011.552242.Google Scholar
Looi, C. Y., Lim, J., Sella, F., et al. 2017. ‘Transcranial Random Noise Stimulation and Cognitive Training to Improve Learning and Cognition of the Atypically Developing Brain: A Pilot Study’. Scientific Reports 7 (1): 1–10.Google Scholar
Lopez, M., Ruiz, M. O., Rovnaghi, C. R., et al. 2021. ‘The Social Ecology of Childhood and Early Life Adversity’. Pediatric Research 89 (2): 353–67.Google Scholar
Losen, D. J., and Welner, K. G.. 2001. ‘Disabling Discrimination in Our Public Schools: Comprehensive Legal Challenges to Inappropriate and Inadequate Special Education Services for Minority Children’. The Harvard Civil Rights – Civil Liberties Law Review. 36: 407.Google Scholar
Loveless, T. 2015. ‘2015 Brown Center Report on American Education: How Well Are American Students Learning?’ Brookings. March 24, 2015. www.brookings.edu/research/2015-brown-center-report-on-american-education-how-well-are-american-students-learning/.Google Scholar
Lovett, M. W., Lacerenza, L., and Borden, S. L.. 2000. ‘Putting Struggling Readers on the PHAST Track: A Program to Integrate Phonological and Strategy-Based Remedial Reading Instruction and Maximize Outcomes’. Journal of Learning Disabilities 33 (5): 458–76.Google Scholar
Lovett, M. W., Lacerenza, L., De Palma, M., and Frijters, J. C.. 2012. ‘Evaluating the Efficacy of Remediation for Struggling Readers in High School’. Journal of Learning Disabilities 45 (2): 151–69.Google Scholar
Lovett, M. W., Lacerenza, L., Steinbach, K. A., and De Palma, M.. 2014. ‘Development and Evaluation of a Research-Based Intervention Program for Children and Adolescents with Reading Disabilities’. Perspectives on Language and Literacy 40 (3): 21–31.Google Scholar
Luby, J. L., Baram, T. Z., Rogers, C. E., and Barch, D. M.. 2020. ‘Neurodevelopmental Optimization after Early-Life Adversity: Cross-Species Studies to Elucidate Sensitive Periods and Brain Mechanisms to Inform Early Intervention’. Trends in Neurosciences 43 (10): 744–51.Google Scholar
Luciano, M., Evans, D. M., Hansell, N. K., et al. 2013. ‘A Genome-Wide Association Study for Reading and Language Abilities in Two Population Cohorts’. Genes, Brain, and Behavior 12 (6): 645–52.Google Scholar
Ludwig, K. U., Schumacher, J., Schulte-Körne, G., et al. 2008. ‘Investigation of the DCDC2 Intron 2 Deletion/compound Short Tandem Repeat Polymorphism in a Large German Dyslexia Sample’. Psychiatric Genetics 18 (6): 310–12.Google Scholar
Luke, K.-K., Liu, H.-L., Wai, Y.-Y., Wan, Y.-L., and Tan, L. H.. 2002. ‘Functional Anatomy of Syntactic and Semantic Processing in Language Comprehension’. Human Brain Mapping 16 (3): 133–45.Google Scholar
Lundberg, I., Frost, J., and Petersen, O.-P.. 1988. ‘Effects of an Extensive Program for Stimulating Phonological Awareness in Preschool Children’. Reading Research Quarterly 23 (3): 263–84. https://doi.org/10.1598/rrq.23.3.1.Google Scholar
Lu, Y., Ma, M., Chen, G., and Zhou, X.. 2021. ‘Can Abacus Course Eradicate Developmental Dyscalculia’. Psychology in the Schools 58 (2): 235–51.Google Scholar
Lyons, I. M., and Beilock, S. L.. 2011. ‘Numerical Ordering Ability Mediates the Relation between Number-Sense and Arithmetic Competence’. Cognition 121 (2): 256–61.Google Scholar
Macizo, P., Herrera, A., Román, P., and Martín, M. Cruz. 2011. ‘The Processing of Two-Digit Numbers in Bilinguals’. British Journal of Psychology 102 (3): 464–77.Google Scholar
Mahé, G., Pont, C., Zesiger, P., and Laganaro, M.. 2018. ‘The Electrophysiological Correlates of Developmental Dyslexia: New Insights from Lexical Decision and Reading Aloud in Adults’. Neuropsychologia 121 (December): 19–27.Google Scholar
Maïonchi-Pino, N., Magnan, A., and Ecalle, J.. 2010. ‘The Nature of the Phonological Processing in French Dyslexic Children: Evidence for the Phonological Syllable and Linguistic Features’ Role in Silent Reading and Speech Discrimination’. Annals of Dyslexia 60 (2): 123–50.Google Scholar
Makita, K. 1968. ‘The Rarity of Reading Disability in Japanese Children’. The American Journal of Orthopsychiatry 38 (4): 599–614.Google Scholar
Mann, B. 2014. ‘Equity and Equality Are Not Equal’. The Education Trust. https://edtrust.org/the-equity-line/equity-and-equality-are-not-equal/.Google Scholar
Manolitsis, G., Georgiou, G. K., and Tziraki, N.. 2013. ‘Examining the Effects of Home Literacy and Numeracy Environment on Early Reading and Math Acquisition’. Early Childhood Research Quarterly 28 (4): 692–703.Google Scholar
Marchesotti, S., Nicolle, J., Merlet, I., Arnal, L. H., Donoghue, J. P., and Giraud, A.-L.. 2020. ‘Selective Enhancement of Low-Gamma Activity by tACS Improves Phonemic Processing and Reading Accuracy in Dyslexia’. PLoS Biology 18 (9): e3000833.CrossRefGoogle ScholarPubMed
Marioni, R. E., Davies, G., Hayward, C., et al. 2014. ‘Molecular Genetic Contributions to Socioeconomic Status and Intelligence’. Intelligence 44 (May): 26–32.Google Scholar
Marjou, Xavier. 2019. ‘OTEANN: Estimating the Transparency of Orthographies with an Artificial Neural Network’. arXiv [cs.CL]. arXiv. http://arxiv.org/abs/1912.13321.Google Scholar
Mark, W., and Dowker, A.. 2015. ‘Linguistic Influence on Mathematical Development Is Specific rather than Pervasive: Revisiting the Chinese Number Advantage in Chinese and English Children’. Frontiers in Psychology 6 (February): 203.Google Scholar
Maroto, M., Pettinicchio, D., and Patterson, A. C.. 2019. ‘Hierarchies of Categorical Disadvantage: Economic Insecurity at the Intersection of Disability, Gender, and Race’. Gender & Society: Official Publication of Sociologists for Women in Society 33 (1): 64–93.Google Scholar
Marshall, A. T., Betts, S., Kan, E. C., McConnell, R., Lanphear, B. P., and Sowell, E. R.. 2020. ‘Association of Lead-Exposure Risk and Family Income with Childhood Brain Outcomes’. Nature Medicine 26 (1): 91–7.Google Scholar
Marsh, H. W., Abduljabbar, A. S., Parker, P. D., et al. 2015. ‘The Internal/External Frame of Reference Model of Self-Concept and Achievement Relations: Age-Cohort and Cross-Cultural Differences’. American Educational Research Journal 52 (1): 168–202.Google Scholar
Martin, A., Kronbichler, M., and Richlan, F.. 2016. ‘Dyslexic Brain Activation Abnormalities in Deep and Shallow Orthographies: A Meta‐analysis of 28 Functional Neuroimaging Studies’. Human Brain Mapping 37 (7): 2676–99. https://doi.org/10.1002/hbm.23202.Google Scholar
Massand, E. and Karmiloff-Smith, A.. 2015. ‘Cascading Genetic and Environmental Effects on Development: Implications for Intervention’. In Mitchell, K. J. (ed.),The Genetics of Neurodevelopmental Disorders, 275–88. John Wiley & Sons, Inc.Google Scholar
Master, A., Cheryan, S., Moscatelli, A., and Meltzoff, A. N.. 2017. ‘Programming Experience Promotes Higher STEM Motivation among First-Grade Girls’. Journal of Experimental Child Psychology 160: 92–106. https://doi.org/10.1016/j.jecp.2017.03.013.Google Scholar
Maughan, B., and Carroll, J.. 2006. ‘Literacy and Mental Disorders’. Current Opinion in Psychiatry 19 (4): 350.Google Scholar
Mayes, S. D., and Calhoun, S. L.. 2006. ‘Frequency of Reading, Math, and Writing Disabilities in Children with Clinical Disorders’. Learning and Individual Differences 16 (2): 145–57.Google Scholar
Mazzocco, M. M. M., Feigenson, L., and Halberda, J.. 2011. ‘Preschoolers’ Precision of the Approximate Number System Predicts Later School Mathematics Performance’. PloS One 6 (9): e23749.Google Scholar
McArthur, G., Castles, A., Kohnen, S., et al. 2015. ‘Sight Word and Phonics Training in Children With Dyslexia’. Journal of Learning Disabilities 48 (4): 391–407.Google Scholar
McArthur, G., Eve, P. M., Jones, K., et al. 2012. ‘Phonics Training for English-Speaking Poor Readers’. Cochrane Database of Systematic Reviews 12 (December): CD009115.Google Scholar
McArthur, G., Sheehan, Y, Badcock, N. A., et al. 2018. ‘Phonics Training for English‐speaking Poor Readers’. Cochrane Database of Systematic Reviews, no. 11. https://doi.org/10.1002/14651858.CD009115.pub3.Google Scholar
McArthur, G., Kohnen, S., Jones, K., et al. 2015. ‘Replicability of Sight Word Training and Phonics Training in Poor Readers: A Randomised Controlled Trial’. PeerJ 3 (May): e922.Google Scholar
McBride, C., Wang, Y., and Cheang, L. M.-L.. 2018. ‘Dyslexia in Chinese’. Current Developmental Disorders Reports 5 (4): 217–25.Google Scholar
McBride-Chang, C. 1999. ‘The ABCs of the ABCs: The Development of Letter-Name and Letter-Sound Knowledge’. Merrill-Palmer Quarterly 45 (2): 285–308.Google Scholar
McBride-Chang, C., Cho, J.-R., Liu, H, et al. 2005. ‘Changing Models across Cultures: Associations of Phonological Awareness and Morphological Structure Awareness with Vocabulary and Word Recognition in Second Graders from Beijing, Hong Kong, Korea, and the United States’. Journal of Experimental Child Psychology 92 (2): 140–60.Google Scholar
McBride-Chang, C., Chung, K. K. H., and Tong, X.. 2011. ‘Copying Skills in Relation to Word Reading and Writing in Chinese Children with and without Dyslexia’. Journal of Experimental Child Psychology 110 (3): 422–33. https://doi.org/10.1016/j.jecp.2011.04.014.Google Scholar
McBride-Chang, C., Lam, F., Lam, C., et al. 2011. ‘Early Predictors of Dyslexia in Chinese Children: Familial History of Dyslexia, Language Delay, and Cognitive Profiles’. Journal of Child Psychology and Psychiatry 52 (2): 204–11. https://doi.org/10.1111/j.1469-7610.2010.02299.x.Google Scholar
McCaskey, U., von Aster, M., O’Gorman Tuura, R, and Kucian, K.. 2017. ‘Adolescents with Developmental Dyscalculia Do Not Have a Generalized Magnitude Deficit – Processing of Discrete and Continuous Magnitudes’. Frontiers in Human Neuroscience 11. https://doi.org/10.3389/fnhum.2017.00102.Google Scholar
McCrink, K., and Wynn, K.. 2004. ‘Large-Number Addition and Subtraction by 9-Month-Old Infants’. Psychological Science 15 (11): 776–81.Google Scholar
McElvany, N., Kortenbruck, M., and Becker, M.. 2008. ‘Lesekompetenz Und Lesemotivation’. Zeitschrift Für Pädagogische Psychologie 22 (34): 207–19. https://doi.org/10.1024/1010-0652.22.34.207.Google Scholar
McEwen, B. S., Bowles, N. P., Gray, J. D., et al. 2015. ‘Mechanisms of Stress in the Brain’. Nature Neuroscience 18 (10): 1353–63.Google Scholar
McGee, R., Prior, M., Williams, S., Smart, D., and Sanson, A.. 2002. ‘The Long-Term Significance of Teacher-Rated Hyperactivity and Reading Ability in Childhood: Findings from Two Longitudinal Studies’. Journal of Child Psychology and Psychiatry 43 (8): 1004–17. https://doi.org/10.1111/1469-7610.00228.Google Scholar
McLeskey, J., Waldron, N. L., and Wornhoff, S. A.. 1990. ‘Factors Influencing the Identification of Black and White Students with Learning Disabilities’. Journal of Learning Disabilities 23 (6): 362–66.Google Scholar
Meaburn, E. L., Harlaar, N., Craig, I. W., Schalkwyk, L. C., and Plomin, R.. 2008. ‘Quantitative Trait Locus Association Scan of Early Reading Disability and Ability Using Pooled DNA and 100K SNP Microarrays in a Sample of 5760 Children’. Molecular Psychiatry 13 (7): 729–40.Google Scholar
Meaney, M. J. 2010. ‘Epigenetics and the Biological Definition of Gene × Environment Interactions’. Child Development. https://doi.org/10.1111/j.1467-8624.2009.01381.x.Google Scholar
Mehan, H., Hertweck, A., and Meihls, J. L. 1986. Handicapping the Handicapped: Decision Making in Students’ Educational Careers. Stanford University Press.Google Scholar
Meier, M. H., Slutske, W. S., Heath, A. C., and Martin, N. G.. 2011. ‘Sex Differences in the Genetic and Environmental Influences on Childhood Conduct Disorder and Adult Antisocial Behavior’. Journal of Abnormal Psychology 120 (2): 377–88.Google Scholar
Mejía-Rodríguez, A. M., Luyten, H, and Meelissen, M. R. M.. 2020. ‘Gender Differences in Mathematics Self-Concept Across the World: An Exploration of Student and Parent Data of TIMSS 2015’. International Journal of Science and Mathematics Education 19: 1229–50. https://doi.org/10.1007/s10763-020-10100-x.Google Scholar
Mejias, S., Grégoire, J., and Noël, M.-P.. 2012. ‘Numerical Estimation in Adults with and without Developmental Dyscalculia’. Learning and Individual Differences 22 (1): 164–70.Google Scholar
Melby-Lervåg, M., and Lervåg, A.. 2012. ‘Oral Language Skills Moderate Nonword Repetition Skills in Children With Dyslexia: A Meta-Analysis of the Role of Nonword Repetition Skills in Dyslexia’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 16 (1): 1–34.Google Scholar
Melby-Lervåg, M., Redick, T. S., and Hulme, C.. 2016. ‘Working Memory Training Does Not Improve Performance on Measures of Intelligence or Other Measures of ‘Far Transfer’: Evidence From a Meta-Analytic Review’. Perspectives on Psychological Science: A Journal of the Association for Psychological Science 11 (4): 512–34.Google Scholar
Melhuish, E., Quinn, L., Sylva, K., et al. 2013. ‘Preschool Affects Longer Term Literacy and Numeracy: Results from a General Population Longitudinal Study in Northern Ireland’. School Effectiveness and School Improvement 24 (2): 234–50.Google Scholar
Meng, Z.-L., Wydell, T. N., and Bi., H.-Y. 2019. ‘Visual-Motor Integration and Reading Chinese in Children With/without Dyslexia’. Reading and Writing 32: 493–510. https://doi.org/10.1007/s11145-018-9876-z.Google Scholar
Menon, V. 2016. ‘Working Memory in Children’s Math Learning and Its Disruption in Dyscalculia’. Current Opinion in Behavioral Sciences 10 (August): 125–32.Google Scholar
Mercer, J. R. 1973. Labeling the Mentally Retarded: Clinical and Social System Perspectives on Mental Retardation. University of California Press.Google Scholar
Michels, L., O’Gorman, R., and Kucian, K.. 2018. ‘Functional Hyperconnectivity Vanishes in Children with Developmental Dyscalculia after Numerical Intervention’. Developmental Cognitive Neuroscience 30 (April): 291–303.Google Scholar
Michie, S., Fixsen, D, Grimshaw, J. M., and Eccles, M. P.. 2009. ‘Specifying and Reporting Complex Behaviour Change Interventions: The Need for a Scientific Method’. Implementation Science 4 (40). https://doi.org/10.1186/1748-5908-4-40.Google Scholar
Miciak, J., and Fletcher, J. M.. 2019. ‘The Identification of Reading Disabilities’. In Kilpatrick, D., Joshi, R., and Wagner, R. (eds) Reading Development and Difficulties. Springer. https://doi.org/10.1007/978-3-030-26550-2_7.Google Scholar
Miles, C. 1895. ‘A Study of Individual Psychology’. The American Journal of Psychology 6 (4): 534–58.Google Scholar
Miles, T. R., Haslum, M. N., and Wheeler, T. J.. 1998. ‘Gender Ratio in Dyslexia’. Annals of Dyslexia 48 (1): 27–55.Google Scholar
Miller, B., Taylor, K., and Ryder, R.. 2019. ‘Introduction to Special Topic: Serving Children with Disabilities Within Multitiered Systems of Support’. AERA Open 5 (2). https://doi.org/10.1177/2332858419853796.Google Scholar
Miller, D. I., and Halpern, D. F.. 2014. ‘The New Science of Cognitive Sex Differences’. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2013.10.011.Google Scholar
Miller, E. B., Farkas, G., Lowe Vandell, D, and Duncan, G. J.. 2014. ‘Do the Effects of Head Start Vary by Parental Preacademic Stimulation?’ Child Development 85 (4): 1385–1400.Google Scholar
Miller, K. F., Kelly, M., and Zhou, X.. 2005. ‘Learning Mathematics in China and the United States: Cross-Cultural Insights into the Nature and Course of Preschool Mathematical Development’. In Handbook of Mathematical Cognition, edited by Campbell, J. I. D., 508: 163–77. Psychology Press.Google Scholar
Mix, K. S. 2019. ‘Why Are Spatial Skill and Mathematics Related?’ Child Development Perspectives 13 (2): 121–6.Google Scholar
Mix, K. S., Levine, S. C., Cheng, Y.-L., et al. 2016. ‘Separate but Correlated: The Latent Structure of Space and Mathematics across Development’. Journal of Experimental Psychology. General 145 (9): 1206–27.Google Scholar
Mo, C., Yu, M., Seger, C., and Mo., L. 2015. ‘Holistic Neural Coding of Chinese Character Forms in Bilateral Ventral Visual System’. Brain and Language 141: 28–39. https://doi.org/10.1016/j.bandl.2014.11.008.Google Scholar
Moeller, K., Fischer, U., Cress, U., and Nuerk, H.-C.. 2012. ‘Diagnostics and Intervention in Developmental Dyscalculia: Current Issues and Novel Perspectives’. In Reading, Writing, Mathematics and the Developing Brain: Listening to Many Voices, edited by Breznitz, Z., Rubinsten, O., Molfese, V. J., and Molfese, D. L, 233–75. Springer Netherlands.Google Scholar
Moeller, K., Shaki, S, Göbel, S. M., and Nuerk, H.-C.. 2015. ‘Language Influences Number Processing–a Quadrilingual Study’. Cognition 136 (March): 150–5.Google Scholar
Moeller, K., Zuber, J., Olsen, N., Nuerk, H.-C., and Willmes, K.. 2015. ‘Intransparent German Number Words Complicate Transcoding: A Translingual Comparison with Japanese’. Frontiers in Psychology 6 (June): 740.Google Scholar
Mohd, S., Elleeiana, N., Hamzaid, N. A., Pingguan Murphy, B., and Lim, E.. 2016. ‘Development of Computer Play Pedagogy Intervention for Children with Low Conceptual Understanding in Basic Mathematics Operation Using the Dyscalculia Feature Approach’. Interactive Learning Environments 24 (7): 1477–96.Google Scholar
Mohr, J. P. 2006. ‘Broca’s Area and Broca’s Aphasia (1976)’. Broca’s Region. Oxford Scholarship online: https://doi.org/10.1093/acprof:oso/9780195177640.003.0027.Google Scholar
Moll, K., Ramus, F., Bartling, J., et al. 2014. ‘Cognitive Mechanisms Underlying Reading and Spelling Development in Five European Orthographies’. Learning and Instruction 29 (February): 65–77.Google Scholar
Monei, T., and Pedro, A.. 2017. ‘A Systematic Review of Interventions for Children Presenting with Dyscalculia in Primary Schools’. Educational Psychology in Practice 33 (3): 277–93.Google Scholar
Mononen, R., Aunio, P., Koponen, T., and Aro, M.. 2015. ‘A Review of Early Numeracy Interventions for Children at Risk in Mathematics’. International Journal of Early Childhood Special Education, 6, 25–54.Google Scholar
Mononen, R., Aunio, P., Koponen, T., et al. 2014. ‘Investigating RightStart Mathematics Kindergarten Instruction in Finland’. Journal of Early Childhood Education Research 3 (1): 2–26. https://helda.helsinki.fi/bitstream/handle/10138/232677/Mononen_Aunio_Koponen_issue3_1b.pdf?sequence=1.Google Scholar
Moody, H. A., Darden, J. T., and Pigozzi, B. W.. 2016. ‘The Relationship of Neighborhood Socioeconomic Differences and Racial Residential Segregation to Childhood Blood Lead Levels in Metropolitan Detroit’. Journal of Urban Health: Bulletin of the New York Academy of Medicine 93 (5): 820–39.Google Scholar
Moore, D. S. 2017. ‘Behavioral Epigenetics’. Wiley Interdisciplinary Reviews: Systems Biology and Medicine 9 (1): e1333.Google Scholar
Moore, D. S., and Shenk, D.. 2017. ‘The Heritability Fallacy’. Wiley Interdisciplinary Reviews: Cognitive Science 8 (1–2): e1400.Google Scholar
Moran, A. S., Swanson, H. L., Gerber, M. M., and Fung, W.. 2014. ‘The Effects of Paraphrasing Interventions on Problem-Solving Accuracy for Children at Risk for Math Disabilities’. Learning Disabilities Research & Practice: A Publication of the Division for Learning Disabilities, Council for Exceptional Children 29 (3): 97–105.Google Scholar
Moreau, D., Wilson, A. J., McKay, N. S., Nihill, K., and Waldie, K. E.. 2018. ‘No Evidence for Systematic White Matter Correlates of Dyslexia and Dyscalculia’. NeuroImage. Clinical 18 (February): 356–66.Google Scholar
Morgan, P. L., Farkas, G., Hillemeier, M. M., et al. 2015. ‘Minorities Are Disproportionately Underrepresented in Special Education: Longitudinal Evidence Across Five Disability Conditions’. Educational Researcher 44 (5): 278–92.Google Scholar
Morishita, H., and Hensch, T. K.. 2008. ‘Critical Period Revisited: Impact on Vision’. Current Opinion in Neurobiology 18 (1): 101–7.Google Scholar
Morris, A. P., Voight, B. F., Teslovich, T. M., et al. 2012. ‘Large-Scale Association Analysis Provides Insights into the Genetic Architecture and Pathophysiology of Type 2 Diabetes’. Nature Genetics 44 (9): 981–90.Google Scholar
Morris, R. D., Lovett, M. W., Wolf, M, et al. 2012. ‘Multiple-Component Remediation for Developmental Reading Disabilities: IQ, Socioeconomic Status, and Race as Factors in Remedial Outcome’. Journal of Learning Disabilities 45 (2): 99–127.Google Scholar
Morsanyi, K., van Bers, B. M. C. W, McCormack, T., and McGourty, J.. 2018. ‘The Prevalence of Specific Learning Disorder in Mathematics and Comorbidity with Other Developmental Disorders in Primary School-Age Children’. British Journal of Psychology 109 (4): 917–40.Google Scholar
Mughal, M. K., Ginn, C. S., Perry, R. L., and Benzies, K. M.. 2016. ‘Longitudinal Effects of a Two-Generation Preschool Programme on Receptive Language Skill in Low-Income Canadian Children to Age 10 Years’. Early Child Development and Care 186 (8): 1316–26.Google Scholar
Müller, B., Schaadt, G., Boltze, J., et al. 2017. ‘ATP2C2andDYX1C1are Putative Modulators of Dyslexia-Related MMR’. Brain and Behavior 7 (1): e00851. https://doi.org/10.1002/brb3.851.Google Scholar
Murphy, K. A., Jogia, J., and Talcott, J. B.. 2019. ‘On the Neural Basis of Word Reading: A Meta-Analysis of fMRI Evidence Using Activation Likelihood Estimation’. Journal of Neurolinguistics 49 (February): 71–83.Google Scholar
Murphy, M. M., Mazzocco, M. M. M., Hanich, L. B., and Early, M. C.. 2007. ‘Cognitive Characteristics of Children With Mathematics Learning Disability (MLD) Vary as a Function of the Cutoff Criterion Used to Define MLD’. Journal of Learning Disabilities 40 (5): 458–78. https://doi.org/10.1177/00222194070400050901.Google Scholar
Muter, V., Hulme, C., Snowling, M. J., and Stevenson, J.. 2004. ‘Phonemes, Rimes, Vocabulary, and Grammatical Skills as Foundations of Early Reading Development: Evidence from a Longitudinal Study’. Developmental Psychology 40 (5): 665–81.Google Scholar
Muter, V., and Snowling, M.. 1998. ‘Concurrent and Longitudinal Predictors of Reading: The Role of Metalinguistic and Short-Term Memory Skills’. Reading Research Quarterly 33 (3): 320–37.Google Scholar
Muter, V., Hulme, C., Snowling, M., and Taylor, S.. 1998. ‘Segmentation, Not Rhyming, Predicts Early Progress in Learning to Read’. Journal of Experimental Child Psychology 71 (1): 3–27.Google Scholar
Nagel, Stuart. 1994. Encyclopedia of Policy Studies, 2nd ed. CRC Press.Google Scholar
Nag, S. 2013. ‘Low Literacy Attainments in School and Approaches to Diagnosis: An Exploratory Study’. Contemporary Education Dialogue 10 (2): 197–221.Google Scholar
Nag, S., Chiat, S., Torgerson, C., and Snowling, M. J.. 2014. ‘Literacy, Foundation Learning and Assessment in Developing Countries’. DFID Publication. www.globalreadingnetwork.net/sites/default/files/media/file/Literacy-foundation-learning-assessment.pdf.Google Scholar
Nag, S., and Snowling, M. J.. 2011. ‘Cognitive Profiles of Poor Readers of Kannada’. Reading and Writing 24 (6): 657–76.Google Scholar
Nag, S., Vagh, S.r B., Dulay, K. M., and Snowling, M. J.. 2018. ‘Home Language, School Language and Children’s Literacy Attainments: A Systematic Review of Evidence from Low‐ and Middle‐income Countries’. Review of Education 7 (1): 91–150. https://doi.org/10.1002/rev3.3130.Google Scholar
Nag, S., and Snowling, M. J.. 2012. ‘School Underachievement and Specific Learning Difficulties’. https://www.neuroscience.ox.ac.uk/publications/672400.Google Scholar
Nag, S. (2011). Re-thinking support: the hidden school-to-work challenges for individuals with Special Needs. International Journal of Educational and Vocational Guidance. 11(2), 125 – 137. doi: 10.1007/s10775-011-9203-6Google Scholar
Nagy, W., Berninger, V., Abbott, R., Vaughan, K., and Vermeulen, K.. 2003. ‘Relationship of Morphology and Other Language Skills to Literacy Skills in At-Risk Second-Grade Readers and At-Risk Fourth-Grade Writers’. Journal of Educational Psychology 95 (4): 730–42.Google Scholar
Nakamura, K., Kuo, W.-J., Pegado, F., et al. 2012. ‘Universal Brain Systems for Recognizing Word Shapes and Handwriting Gestures during Reading’. Proceedings of the National Academy of Sciences of the United States of America 109 (50): 20762–67.Google Scholar
Näslund, J. C., and Schneider, W.. 1991. ‘Longitudinal Effects of Verbal Ability, Memory Capacity, and Phonological Awareness on Reading Performance’. European Journal of Psychology of Education. https://doi.org/10.1007/bf03172772.Google Scholar
National Center on Response to Intervention. 2010. Essential Components of RTI – A Closer Look at Response to Intervention. US Department of Education, Office of Special Education Programs, National Center on Response to Intervention. http://files.eric.ed.gov/fulltext/ED526858.pdf.Google Scholar
National Early Literacy Panel (US). 2008. Developing Early Literacy: Report of the National Early Literacy Panel. https://lincs.ed.gov/publications/pdf/NELPReport09.pdf.Google Scholar
‘National Education Policy, 2020’. n.d. Accessed July 29, 2021. www.education.gov.in/sites/upload_files/mhrd/files/NEP_Final_English_0.pdf.Google Scholar
National Reading Panel (US). 2000. Report of the National Reading Panel: Teaching Children to Read: An Evidence-Based Assessment of the Scientific Research Literature on Reading and Its Implications for Reading Instruction: Reports of the Subgroups. www.nichd.nih.gov/publications/pubs/nrp/smallbook.Google Scholar
National Research Council. 2002. Minority Students in Special and Gifted Education. Edited by Donovan, M. S. and Cross, C. T.. The National Academies Press.Google Scholar
Nation, K. 2005. ‘Children’s Reading Comprehension Difficulties’. In Snowling, M. J and Hulme, C (eds.), The Science of Reading: A Handbook, chapter 14. Blackwell Publishing Ltd . https://doi.org/10.1002/9780470757642.ch14.Google Scholar
Nelson, J. R., Liu, Y., Fiez, J., and Perfetti, C. A.. 2009. ‘Assimilation and Accommodation Patterns in Ventral Occipitotemporal Cortex in Learning a Second Writing System’. Human Brain Mapping 30: 810–20. https://doi.org/10.1002/hbm.20551.Google Scholar
Nelson, K., and Fivush, R.. 2004. ‘The Emergence of Autobiographical Memory: A Social Cultural Developmental Theory’. Psychological Review 111 (2): 486–511.Google Scholar
Newcombe, N. S., Lloyd, M. E., and Ratliff, K. R.. 2007. ‘Development of Episodic and Autobiographical Memory: A Cognitive Neuroscience Perspective’. Advances in Child Development and Behavior 35: 37–85.Google Scholar
Newstead, K. 1998. ‘Aspects of Children’s Mathematics Anxiety’. Educational Studies in Mathematics 36 (1): 53–71.Google Scholar
Nguyen, T., Watts, T. W., Duncan, G.J., et al. 2016. ‘Which Preschool Mathematics Competencies Are Most Predictive of Fifth Grade Achievement?’ Early Childhood Research Quarterly 36 (July): 550–60.Google Scholar
Nicolson, R. I., and Fawcett, A. J.. 2007. ‘Procedural Learning Difficulties: Reuniting the Developmental Disorders?’ Trends in Neurosciences 30 (4): 135–41.Google Scholar
Nieder, A., and Miller, E. K.. 2003. ‘Coding of Cognitive Magnitude: Compressed Scaling of Numerical Information in the Primate Prefrontal Cortex’. Neuron 7 (1): 149–57.Google Scholar
Niklas, F., and Schneider, W.. 2014. ‘Casting the Die before the Die Is Cast: The Importance of the Home Numeracy Environment for Preschool Children’. European Journal of Psychology of Education 29 (3): 327–45.Google Scholar
Nitsche, M. A., Fricke, K., Henschke, U., et al. 2003. ‘Pharmacological Modulation of Cortical Excitability Shifts Induced by Transcranial Direct Current Stimulation in Humans’. The Journal of Physiology 553 (Pt 1): 293–301.Google Scholar
Noort, M. den, den Noort, M., Struys, E., and Bosch, P. 2015. ‘Transcranial Magnetic Stimulation Research on Reading and Dyslexia: A New Clinical Intervention Technique for Treating Dyslexia?’ Neuroimmunology and Neuroinflammation 2: 145–52. https://doi.org/10.4103/2347-8659.157967.Google Scholar
Norbury, C. F., Gooch, D., Wray, C., et al. 2016. ‘The Impact of Nonverbal Ability on Prevalence and Clinical Presentation of Language Disorder: Evidence from a Population Study’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 57 (11): 1247–57.Google Scholar
Nores, M., and Barnett, W. S.. 2010. ‘Benefits of Early Childhood Interventions across the World: (Under) Investing in the Very Young’. Economics of Education Review 29 (2): 271–82.Google Scholar
Nosworthy, N., Bugden, S., Archibald, L., Evans, B., and Ansari, D.. 2013. ‘A Two-Minute Paper-and-Pencil Test of Symbolic and Nonsymbolic Numerical Magnitude Processing Explains Variability in Primary School Children’s Arithmetic Competence’. PLoS ONE 87 (7): e67918. https://doi.org/10.1371/journal.pone.0067918.Google Scholar
Novick, M. R. 1966. ‘The Axioms and Principal Results of Classical Test Theory’. Journal of Mathematical Psychology 3 (1): 1–18.Google Scholar
Nuerk, H.-C., Patro, K., Cress, U., Schild, U., Friedrich, C. K., and Göbel, S. M.. 2015. ‘How Space-Number Associations May Be Created in Preliterate Children: Six Distinct Mechanisms’. Frontiers in Psychology 6 (March): 215.Google Scholar
Nys, J., Ventura, P., Fernandes, T., et al. 2013. ‘Does Math Education Modify the Approximate Number System? A Comparison of Schooled and Unschooled Adults’. Trends in Neuroscience and Education 2 (1): 13–22.Google Scholar
Ober, T. M., Brooks, P. J., Homer, B. D., and Rindskopf, D.. 2020. ‘Executive Functions and Decoding in Children and Adolescents: A Meta-Analytic Investigation’. Educational Psychology Review 32: 1–29.Google Scholar
O’Connor, P. D., Sofo, F., Kendall, L., and Olsen, G.. 1990. ‘Reading Disabilities and the Effects of Colored Filters’. Journal of Learning Disabilities 23 (10): 597–603, 620.Google Scholar
Odden, A. R., ed. 1991. Education Policy Implementation. SUNY Series, Educational Leadership. State University of New York Press.Google Scholar
Odic, D., and Starr, A.. 2018. ‘An Introduction to the Approximate Number System’. Child Development Perspectives 12 (4): 223–29.Google Scholar
OECD. 2011. Starting Strong III: A Quality Toolbox for Early Childhood Education and Care: A Quality Toolbox for Early Childhood Education and Care. OECD Publishing.Google Scholar
OECD 2019. PISA 2018 Results (Volume I): What Students Know and Can Do: What Students Know and Can Do. OECD Publishing.Google Scholar
Okbay, A., Beauchamp, J. P., Fontana, M. A., et al. 2016. ‘Genome-Wide Association Study Identifies 74 Loci Associated with Educational Attainment’. Nature 533 (7604): 539–42.Google Scholar
Oliver, M. L., Shapiro, T. M., and Shapiro, T.. 2006. Black Wealth, White Wealth: A New Perspective on Racial Inequality. Taylor & Francis.Google Scholar
Olsson, L., Östergren, R., and Träff, U.. 2016. ‘Developmental Dyscalculia: A Deficit in the Approximate Number System or an Access Deficit?’ Cognitive Development 39 (July): 154–67.Google Scholar
O’Malley, K. J., Francis, D. J., Foorman, B. R., Fletcher, J. M., and Swank, P. R.. 2002. ‘Growth in Precursor and Reading-Related Skills: Do Low-Achieving and IQ-Discrepant Readers Develop Differently?’ Learning Disabilities Research & Practice: A Publication of the Division for Learning Disabilities, Council for Exceptional Children 17 (1): 19–34.Google Scholar
O’Malley, Patricia, Jenkins, Sandi, Wesley, Brooke, et al. 2013. ‘Effectiveness of Using iPads to Build Math Fluency’. Paper presented at 2013 Council for Exceptional Children Annual Meeting in San Antonio, Texas. http://files.eric.ed.gov/fulltext/ED541158.pdf.Google Scholar
Ong-Dean, C. 2006. ‘High Roads and Low Roads: Learning Disabilities in California, 1976–1998’. Sociological Perspectives: SP: Official Publication of the Pacific Sociological Association 49 (1): 91–113.Google Scholar
Ong-Dean, C 2009. Distinguishing Disability: Parents, Privilege, and Special Education. University of Chicago Press.Google Scholar
Osher, D., Kelly, D. L., Tolani-Brown, N., Shors, L., and Chen, C.-S.. 2009. ‘UNICEF Child Friendly Schools Programming: Global Evaluation Final Report’. Washington, DC: American Institutes for Research. http://humanitarianlibrary.org/sites/default/files/2014/02/cfs_executive_summary_v2r.pdf.Google Scholar
Oswald, D. P., Coutinho, M. J., Best, A. M., and Nguyen, N.. 2001. ‘Impact of Sociodemographic Characteristics on the Identification Rates of Minority Students as Having Mental Retardation’. Mental Retardation 39 (5): 351–67.Google Scholar
Palm, U., Segmiller, F. M., Epple, A. N., et al. 2016. ‘Transcranial Direct Current Stimulation in Children and Adolescents: A Comprehensive Review’. Journal of Neural Transmission 123 (10): 1219–34.Google Scholar
Park, J., Bermudez, V., Roberts, R. C., and Brannon, E. M.. 2016. ‘Non-Symbolic Approximate Arithmetic Training Improves Math Performance in Preschoolers’. Journal of Experimental Child Psychology 152 (December): 278–93.Google Scholar
Parsons, S., Bynner, J., and National Research and Development Centre for Adult Literacy and Numeracy. 2005. Does Numeracy Matter More? https://core.ac.uk/download/pdf/111651.pdf.Google Scholar
Partanen, M., and Siegel, L. S.. 2014. ‘Long-Term Outcome of the Early Identification and Intervention of Reading Disabilities’. Reading and Writing 27: 665–84. https://doi.org/10.1007/s11145-013-9472-1.Google Scholar
Partanen, M., Siegel, L. S., and Giaschi, D. E.. 2019. ‘Longitudinal Outcomes of an Individualized and Intensive Reading Intervention for Third Grade Students’. Dyslexia, no. dys.1616 (April). https://doi.org/10.1002/dys.1616.Google Scholar
Passolunghi, M. C., Vercelloni, B., and Schadee, H.. 2007. ‘The Precursors of Mathematics Learning: Working Memory, Phonological Ability and Numerical Competence’. Cognitive Development 22 (2): 165–84. https://doi.org/10.1016/j.cogdev.2006.09.001.Google Scholar
Pastore, N. 1949. The Nature-Nurture Controversy. King’s Crown Press.Google Scholar
Paulesu, E., McCrory, E., Fazio, F., et al. 2000. ‘A Cultural Effect on Brain Function’. Nature Neuroscience 3: 91–6. https://doi.org/10.1038/71163.Google Scholar
Paulesu, E., Danelli, L., and Berlingeri, M.. 2014. ‘Reading the Dyslexic Brain: Multiple Dysfunctional Routes Revealed by a New Meta-Analysis of PET and fMRI Activation Studies’. Frontiers in Human Neuroscience 8 (November): 830.Google Scholar
Paulesu, E., Démonet, J. F., Fazio, F., et al. 2001. ‘Cultural Diversity and Biological Unity in Dyslexia’. NeuroImage 13 (6): 584. https://doi.org/10.1016/s1053-8119(01)91927-5.Google Scholar
Paxson, C., and Schady, N.. 2007. ‘Cognitive Development among Young Children in Ecuador’. The Journal of Human Resources XLII (1): 49–84.Google Scholar
Peacock, J. L., Marston, L., Marlow, N., Calvert, S. A., and Greenough, A.. 2012. ‘Neonatal and Infant Outcome in Boys and Girls Born Very Prematurely’. Pediatric Research 71 (3): 305–10.Google Scholar
Pearman, F. A., Springer, M. P., Lipsey, M., et al. 2020. ‘Teachers, Schools, and Pre-K Effect Persistence: An Examination of the Sustaining Environment Hypothesis’. Journal of Research on Educational Effectiveness 13 (4): 547–73.Google Scholar
Pedhazur, E. J. 1997. Multiple Regression in Behavioral Research: Explanation and Prediction. Wadsworth Publishing Company.Google Scholar
Peng, P., Lee, K., Luo, J., et al. 2021. ‘Simple View of Reading in Chinese: A One-Stage Meta-Analytic Structural Equation Modeling’. Review of Educational Research 91 (1): 3–33.Google Scholar
Peng, P., Namkung, J., Barnes, M., and Sun, C.. 2016. ‘A Meta-Analysis of Mathematics and Working Memory: Moderating Effects of Working Memory Domain, Type of Mathematics Skill, and Sample Characteristics’. Journal of Educational Psychology 108 (4): 455–73.Google Scholar
Peng, P., Barnes, M., Wang, C., et al. 2018. ‘A Meta-Analysis on the Relation between Reading and Working Memory’. Psychological Bulletin 144 (1): 48–76. https://doi.org/10.1037/bul0000124.Google Scholar
Peng, P., Wang, C., Tao, S., and Sun, C.. 2017. ‘The Deficit Profiles of Chinese Children with Reading Difficulties: A Meta-Analysis’. Educational Psychology Review 29: 513–64. https://doi.org/10.1007/s10648-016-9366-2.Google Scholar
Pennington, B. F. 2006. ‘From Single to Multiple Deficit Models of Developmental Disorders’. Cognition 101 (2): 385–413.Google Scholar
Pennington, B. F., Santerre-Lemmon, L., Rosenberg, J., et al. 2012. ‘Individual Prediction of Dyslexia by Single versus Multiple Deficit Models’. Journal of Abnormal Psychology 121 (1): 212–24.Google Scholar
Perfetti, C. 2007. ‘Reading Ability: Lexical Quality to Comprehension’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 11 (4): 357–83.Google Scholar
Perfetti, C. A., Liu, Y., and Tan, L. H.. 2005. ‘The Lexical Constituency Model: Some Implications of Research on Chinese for General Theories of Reading’. Psychological Review 112 (1): 43–59. https://doi.org/10.1037/0033-295x.112.1.43.Google Scholar
Pesco, D., MacLeod, A. A. A. N., Kay-Raining Bird, E., et al. 2016. ‘A Multi-Site Review of Policies Affecting Opportunities for Children with Developmental Disabilities to Become Bilingual’. Journal of Communication Disorders 63 (September): 15–31.Google Scholar
Peterchev, A. V., Jalinous, R., and Lisanby, S. H.. 2008. ‘A Transcranial Magnetic Stimulator Inducing near-Rectangular Pulses with Controllable Pulse Width (cTMS)’. IEEE Transactions on Bio-Medical Engineering 55 (1): 257–66.Google Scholar
Petermann, F. 2014. ‘Implementationsforschung: Grundbegriffe Und Konzepte’. Psychologische Rundschau 65 (3): 122–8. https://doi.org/10.1026/0033-3042/a000214.Google Scholar
Peters, L., and De Smedt, B.. 2018. ‘Arithmetic in the Developing Brain: A Review of Brain Imaging Studies’. Developmental Cognitive Neuroscience 30): 265–79. https://doi.org/10.1016/j.dcn.2017.05.002.Google Scholar
Peterson, R. L., Arnett, A. B., Pennington, B. F., et al. 2018. ‘Literacy Acquisition Influences Children’s Rapid Automatized Naming’. Developmental Science 21 (3): e12589.Google Scholar
Peterson, R. L., and Pennington, B. F.. 2012. ‘Developmental Dyslexia’. The Lancet 379 (9830): 1997–2007.Google Scholar
Peyre, H., Gérard, C-L, Dupong Vanderhorst, I., et al. 2018. ‘Rééducation Oculomotrice Informatisée Dans La Dyslexie: Essai Clinique Randomisé En Crossover En Population Pédiatrique’. L’Encéphale 44 (3): 247–55.Google Scholar
Pfahl, L., and Powell, J. J. W.. 2011. ‘Legitimating School Segregation. The Special Education Profession and the Discourse of Learning Disability in Germany’. Disability & Society 26 (4): 449–62.Google Scholar
Pfost, M., Blatter, K., Artelt, C., Stanat, P., and Schneider, W.. 2019. ‘Effects of Training Phonological Awareness on Children’s Reading Skills’. Journal of Applied Developmental Psychology 65: 101067. https://doi.org/10.1016/j.appdev.2019.101067.Google Scholar
Piazza, M., Pica, P., Izard, V, Spelke, E. S., and Dehaene, S.. 2013. ‘Education Enhances the Acuity of the Nonverbal Approximate Number System’. Psychological Science 24 (6): 1037–43.Google Scholar
‘PIRLS 2001 International Report’. n.d. Accessed July 22, 2021. https://www.iea.nl/publications/study-reports/international-reports-iea-studies/pirls-2001-international-report.Google Scholar
‘PIRLS 2006 International Report’. n.d. Accessed July 22, 2021. https://timss.bc.edu/pirls2006/intl_rpt.html.Google Scholar
‘PIRLS 2016 – Report’. n.d. Accessed July 22, 2021. http://timssandpirls.bc.edu/pirls2016/international-results/.Google Scholar
Pixner, S., Zuber, J., Heřmanová, V., et al. 2011. ‘One Language, Two Number-Word Systems and Many Problems: Numerical Cognition in the Czech Language’. Research in Developmental Disabilities 32 (6): 2683–9.Google Scholar
Plante, I., de la Sablonnière, R., Aronson, J. M., and Théorêt, M.. 2013. ‘Gender Stereotype Endorsement and Achievement-Related Outcomes: The Role of Competence Beliefs and Task Values’. Contemporary Educational Psychology 38 (3): 225–35. https://doi.org/10.1016/j.cedpsych.2013.03.004.Google Scholar
Poldrack, R. A., Desmond, J. E., Glover, G. H., and Gabrieli, J. D.. 1998. ‘The Neural Basis of Visual Skill Learning: An fMRI Study of Mirror Reading’. Cerebral Cortex 8 (1): 1–10.Google Scholar
Posner, M. I., and Rothbart, M. K.. 2017. ‘Integrating Brain, Cognition and Culture’. Journal of Cultural Cognitive Science 1 (1): 3–15.Google Scholar
Powell, D., and Atkinson, L.. 2020. ‘Unraveling the Links between Rapid Automatized Naming (RAN), Phonological Awareness, and Reading’. Journal of Educational Psychology 113 (4): 706–18. https://doi.org/10.1037/edu0000625.Google Scholar
Preßler, A. L., Könen, T., Hasselhorn, M., and Krajewski, K.. 2014. ‘Cognitive Preconditions of Early Reading and Spelling: A Latent-Variable Approach with Longitudinal Data’. Reading and Writing 27 (2): 383–406.Google Scholar
Pressman, J. L. and Wildavsky, A. 1984. Implementation. University of California Press. Accessed July 29, 2021. https://www.ucpress.edu/book/9780520053311/implementation.Google Scholar
Price, G. R., Holloway, I., Räsänen, P., Vesterinen, M., and Ansari, D.. 2007. ‘Impaired Parietal Magnitude Processing in Developmental Dyscalculia’. Current Biology 17 (24): PR1042–R1043. https://doi.org/10.1016/j.cub.2007.10.013.Google Scholar
Priest, N., Paradies, Y., Trenerry, B., et al. 2013. ‘A Systematic Review of Studies Examining the Relationship between Reported Racism and Health and Wellbeing for Children and Young People’. Social Science & Medicine 95 (October): 115–27.Google Scholar
Prior, M., Smart, D., Sanson, A., and Oberklaid, F.. 2001. ‘Longitudinal Predictors of Behavioural Adjustment in Pre-Adolescent Children’. The Australian and New Zealand Journal of Psychiatry 35 (3): 297–307.Google Scholar
Pritulsky, C., Morano, C., Odean, R., et al. 2020. ‘Spatial Thinking: Why It Belongs in the Preschool Classroom’. Translational Issues in Psychological Science 6 (3): 271–82.Google Scholar
Pröscholdt, M. V., Michalik, A., Schneider, W., et al. 2013. ‘Effekte Kombinierter Förderprogramme Zur Phonologischen Bewusstheit Und Zum Sprachverstehen Auf Die Entwicklung Der Phonologischen Bewusstheit von Kindergartenkindern Mit Und Ohne Migrationshintergrund’. Frühe Bildung 2 (3): 122–32. https://doi.org/10.1026/2191-9186/a000099.Google Scholar
Protopapas, A., Altani, A., and Georgiou, G. K.. 2013. ‘RAN Backward: A Test of the Visual Scanning Hypothesis’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 17 (6): 453–61.Google Scholar
Protopapas, A., Katopodi, K., Altani, A., and Georgiou, G. K.. 2018. ‘Word Reading Fluency as a Serial Naming Task’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 22 (3): 248–63.Google Scholar
Protzko, J. 2016. ‘Does the Raising IQ-Raising G Distinction Explain the Fadeout Effect?’ Intelligence 56 (May): 65–71.Google Scholar
Pruden, S. M., Levine, S. C., and Huttenlocher, J.. 2011. ‘Children’s Spatial Thinking: Does Talk about the Spatial World Matter?’ Developmental Science 14 (6): 1417–30.Google Scholar
Pugh, K. R., Mencl, W. E., Jenner, A. R., et al. 2000. ‘Functional Neuroimaging Studies of Reading and Reading Disability (Developmental Dyslexia)’. Mental Retardation and Developmental Disabilities Research Reviews 6 (3): 207–13. https://doi.org/10.1002/1098-2779(2000)6:3<207::aid-mrdd8>3.0.co;2-p.Google Scholar
Pugh, K. R., Mencl, W. E., Shaywitz, B. A., et al. 2000. ‘The Angular Gyrus in Developmental Dyslexia: Task-Specific Differences in Functional Connectivity Within Posterior Cortex’. Psychological Science. https://doi.org/10.1111/1467-9280.00214.Google Scholar
Pugh, K., and Verhoeven, L.. 2018. ‘Introduction to This Special Issue: Dyslexia Across Languages and Writing Systems’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 22 (1): 1–6.Google Scholar
Purpura, D. J., Hume, L. E., Sims, D. M., and Lonigan, C. J.. 2011. ‘Early Literacy and Early Numeracy: The Value of Including Early Literacy Skills in the Prediction of Numeracy Development’. Journal of Experimental Child Psychology 110 (4): 647–58.Google Scholar
Purpura, D. J., Napoli, A. R., Wehrspann, E. A., and Gold, Z. S.. 2017. ‘Causal Connections between Mathematical Language and Mathematical Knowledge: A Dialogic Reading Intervention’. Journal of Research on Educational Effectiveness 10 (1): 116–37.Google Scholar
Purpura, D. J., and Reid, E. E.. 2016. ‘Mathematics and Language: Individual and Group Differences in Mathematical Language Skills in Young Children’. Early Childhood Research Quarterly 36 (July): 259–68.Google Scholar
Quinn, J. M. 2018. ‘Differential Identification of Females and Males with Reading Difficulties: A Meta-Analysis’. Reading and Writing 31: 1039–61. https://doi.org/10.1007/s11145-018-9827-8.Google Scholar
Rabiner, D., and Coie, J. D.. 2000. ‘Early Attention Problems and Children’s Reading Achievement: A Longitudinal Investigation’. Journal of the American Academy of Child & Adolescent Psychiatry 39 (7): P859–867. https://doi.org/10.1097/00004583-200007000-00014.Google Scholar
Rack, J. P. 2017. ‘Dyslexia: The Phonological Deficit Hypothesis’. In Fawcett, A and Nicolson, R (eds.), Dyslexia in Children, 5–37. Routledge.Google Scholar
Ramaa, S., and Gowramma, I. P.. 2002. ‘A Systematic Procedure for Identifying and Classifying Children with Dyscalculia among Primary School Children in India’. Dyslexia 8 (2): 67–85.Google Scholar
Ramani, G. B., Daubert, E. N., Lin, G. C., et al. 2020. ‘Racing Dragons and Remembering Aliens: Benefits of Playing Number and Working Memory Games on Kindergartners’ Numerical Knowledge’. Developmental Science 23 (4): e12908.Google Scholar
Ramani, G. B., Rowe, M. L., Eason, S. H., and Leech, K. A.. 2015. ‘Math Talk during Informal Learning Activities in Head Start Families’. Cognitive Development 35 (July): 15–33.Google Scholar
Ramani, G. B., and Siegler, R. S.. 2008. ‘Promoting Broad and Stable Improvements in Low-Income Children’s Numerical Knowledge through Playing Number Board Games’. Child Development 79 (2): 375–94.Google Scholar
Ramirez, G., Gunderson, E. A., Levine, S. C., and Beilock, S. L.. 2013. ‘Math Anxiety, Working Memory, and Math Achievement in Early Elementary School’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 14 (2): 187–202.Google Scholar
Ramus, F., Rosen, S., Dakin, S. C., Day, B. L., Castellote, J. M., White, S., & Frith, U. (2003). Theories of developmental dyslexia: Insights from a multiple case study of dyslexic adults. Brain: A Journal of Neurology, 126(Pt 4), 841–865. https://doi.org/10.1093/brain/awg076.Google Scholar
Ranpura, A., Isaacs, E., Edmonds, C., et al. 2013. ‘Developmental Trajectories of Grey and White Matter in Dyscalculia’. Trends in Neuroscience and Education 2 (2): 56–64.Google Scholar
Räsänen, P., Jonna Salminen, A. J. Wilson, P. Aunio, and Dehaene, S.. 2009. ‘Computer-Assisted Intervention for Children with Low Numeracy Skills’. Cognitive Development 24 (4): 450–72.Google Scholar
Rastle, K., and Taylor, J. S. H.. 2018. ‘Print-Sound Regularities Are More Important than Print-Meaning Regularities in the Initial Stages of Learning to Read: Response to Bowers & Bowers (2018)’. Quarterly Journal of Experimental Psychology 71 (7): 1501–5.Google Scholar
Re, A. M., Pedron, M., Tressoldi, P. E., and Lucangeli, D.. 2014. ‘Response to Specific Training for Students With Different Levels of Mathematical Difficulties’. Exceptional Children 80 (3): 337–52.Google Scholar
Reigosa-Crespo, V., Valdés-Sosa, M., Butterworth, B., et al. 2012. ‘Basic Numerical Capacities and Prevalence of Developmental Dyscalculia: The Havana Survey’. Developmental Psychology 48 (1): 123–35.Google Scholar
Reilly, D., Neumann, D. L., and Andrews, G.. 2019. ‘Gender Differences in Reading and Writing Achievement: Evidence from the National Assessment of Educational Progress (NAEP)’. The American Psychologist 74 (4): 445–58.Google Scholar
Reis, A., Araújo, S., Morais, I. S., and Faísca, L.. 2020. ‘Reading and Reading-Related Skills in Adults with Dyslexia from Different Orthographic Systems: A Review and Meta-Analysis’. Annals of Dyslexia 70 (3): 339–68.Google Scholar
Ren, K., and Gunderson, E. A.. 2021. ‘The Dynamic Nature of Children’s Strategy Use after Receiving Accuracy Feedback in Decimal Comparisons’. Journal of Experimental Child Psychology 202 (February): 105015.Google Scholar
Ren, K., Lin, Y., and Gunderson, E. A.. 2019. ‘The Role of Inhibitory Control in Strategy Change: The Case of Linear Measurement’. Developmental Psychology 55 (7): 1389–99.Google Scholar
Resnick, L. B. 1989. ‘Developing Mathematical Knowledge’. American Psychologist 44 (2): 162–69. https://doi.org/10.1037/0003-066x.44.2.162.Google Scholar
Restori, A. F., Katz, G. S., and Lee, H. B.. 2009. ‘A Critique of the IQ / Achievement Discrepancy Model for Identifying Specific Learning Disabilities’. Europe’s Journal of Psychology 5 (4): 128–45.Google Scholar
Ribeiro, F. S., and Santos, F. H.. 2020. ‘Persistent Effects of Musical Training on Mathematical Skills of Children With Developmental Dyscalculia’. Frontiers in Psychology 10: 2888.Google Scholar
Richards, B. A., and Frankland, P. W.. 2017. ‘The Persistence and Transience of Memory’. Neuron 94 (6): 1071–84.Google Scholar
Richlan, F. 2014. ‘Functional Neuroanatomy of Developmental Dyslexia: The Role of Orthographic Depth’. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2014.00347.Google Scholar
Richlan, F., Kronbichler, M., and Wimmer, H.. 2009. ‘Functional Abnormalities in the Dyslexic Brain: A Quantitative Meta-Analysis of Neuroimaging Studies’. Human Brain Mapping 30: 3299–308. https://doi.org/10.1002/hbm.20752.Google Scholar
Rietveld, C. A., Medland, S. E., Derringer, J., et al. 2013. ‘GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment’. Science 340 (6139): 1467–71.Google Scholar
Rios, D. Me., Rios, M. C., Bandeira, I. D., et al. 2018. ‘Impact of Transcranial Direct Current Stimulation on Reading Skills of Children and Adolescents With Dyslexia’. Child Neurology Open 5 (October): 2329048X18798255.Google Scholar
Ritchie, S. J., and Bates, T. C.. 2013. ‘Enduring Links from Childhood Mathematics and Reading Achievement to Adult Socioeconomic Status’. Psychological Science 24 (7): 1301–8.Google Scholar
Ritchie, S. J., Sala, S. Della, and McIntosh, R. D.. 2011. ‘Irlen Colored Overlays Do Not Alleviate Reading Difficulties’. Pediatrics 128 (4): e932–38.Google Scholar
Roberts, G., Quach, J., Spencer-Smith, M., et al. 2016. ‘Academic Outcomes 2 Years After Working Memory Training for Children With Low Working Memory: A Randomized Clinical Trial’. JAMA Pediatrics 170 (5): e154568–e154568.Google Scholar
Robinson, G. L., and Conway, R. N.. 1990. ‘The Effects of Irlen Colored Lenses on Students’ Specific Reading Skills and Their Perception of Ability: A 12-Month Validity Study’. Journal of Learning Disabilities 23 (10): 589–96.Google Scholar
Robinson, G. L., and Foreman, P. J.. 1999. ‘Scotopic sensitivity/Irlen Syndrome and the Use of Coloured Filters: A Long-Term Placebo Controlled and Masked Study of Reading Achievement and Perception of Ability’. Perceptual and Motor Skills 89 (1): 83–113.Google Scholar
Rodic, M., Zhou, X., Tikhomirova, T., et al. 2015. ‘Cross-Cultural Investigation into Cognitive Underpinnings of Individual Differences in Early Arithmetic’. Developmental Science 18 (1): 165–74.Google Scholar
Rogde, K., Melby-Lervåg, M., and Lervåg, A.. 2016. ‘Improving the General Language Skills of Second-Language Learners in Kindergarten: A Randomized Controlled Trial’. Journal of Research on Educational Effectiveness 9 (sup1): 150–70.Google Scholar
Rose, J 2006. Independent Review of the Teaching of Early Reading: Final Report. Department for Education and Skills.Google Scholar
Rosenberg-Lee, M., Ashkenazi, S., Chen, T., et al. 2015. ‘Brain Hyper-Connectivity and Operation-Specific Deficits during Arithmetic Problem Solving in Children with Developmental Dyscalculia’. Developmental Science 18 (3): 351–72. https://doi.org/10.1111/desc.12216.Google Scholar
Roßbach, H.-G., and Hasselhorn, M.. 2014. ‘Lernumwelten in vorschulischen Kindertageseinrichtungen’. In Pädagogische Psychologie, 387. Beltz.Google Scholar
Rossi, S., Hallett, M, Rossini, P. M., Pascual-Leone, A., and Safety of TMS Consensus Group. 2009. ‘Safety, Ethical Considerations, and Application Guidelines for the Use of Transcranial Magnetic Stimulation in Clinical Practice and Research’. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology 120 (12): 2008–39.Google Scholar
Rothe, J., Schulte-Körne, G., and Ise, E.. 2014. ‘Does Sensitivity to Orthographic Regularities Influence Reading and Spelling Acquisition? A 1-Year Prospective Study’. Reading and Writing 27 (7): 1141–61.Google Scholar
Ruan, Y., Georgiou, G. K., Song, S., Li, Y., and Shu, H.. 2018. ‘Does Writing System Influence the Associations between Phonological Awareness, Morphological Awareness, and Reading? A Meta-Analysis’. Journal of Educational Psychology 110 (2): 180–202. https://doi.org/10.1037/edu0000216.Google Scholar
Rubinsten, O., and Tannock, R.. 2010. ‘Mathematics Anxiety in Children with Developmental Dyscalculia’. Behavioral and Brain Functions 6 (46). https://doi.org/10.1186/1744-9081-6-46.Google Scholar
Rueckl, J. G., Paz-Alonso, P. M., Molfese, P. J., et al. 2015. ‘Universal Brain Signature of Proficient Reading: Evidence from Four Contrasting Languages’. Proceedings of the National Academy of Sciences of the United States of America 112 (50): 15510–15.Google Scholar
Rufener, K. S., Krauel, K., Meyer, M., Heinze, H.-J., and Zaehle, T.. 2019. ‘Transcranial Electrical Stimulation Improves Phoneme Processing in Developmental Dyslexia’. Brain Stimulation 12 (4): 930–37.Google Scholar
Rutter, M. 2010. ‘Gene–environment Interplay’. Depression and Anxiety 27 (1): 1–4.Google Scholar
Rutter, M., Caspi, A., Fergusson, D, et al. 2004. ‘Sex Differences in Developmental Reading Disability: New Findings from 4 Epidemiological Studies’. JAMA: The Journal of the American Medical Association 291 (16): 2007–12.Google Scholar
Rutter, M., Moffitt, T. E., and Caspi, A.. 2006. ‘Gene-Environment Interplay and Psychopathology: Multiple Varieties but Real Effects’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 47 (3-4): 226–61.Google Scholar
Rutter, M., and Yule, W.. 1975. ‘The Concept of Specific Reading Retardation’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 16 (3): 181–97.Google Scholar
Saatcioglu, A., and Skrtic, T. M.. 2019. ‘Categorization by Organizations: Manipulation of Disability Categories in a Racially Desegregated School District’. The American Journal of Sociology 125 (1): 184–260.Google Scholar
Sabatier, P. A. 1986. ‘Top-Down and Bottom-Up Approaches to Implementation Research: A Critical Analysis and Suggested Synthesis’. Journal of Public Policy 6 (1): 21–48.Google Scholar
Sabel, C. 2012. ‘Individualised Service Provision and the New Welfare State’. Promoting Inclusive Growth. https://doi.org/10.1787/9789264168305-5-en.Google Scholar
Sampson, R. J., Morenoff, J. D., and Gannon-Rowley, T.. 2002. ‘Assessing ‘Neighborhood Effects’: Social Processes and New Directions in Research’. Annual Review of Sociology 28 (1): 443–78.Google Scholar
Sánchez-León, C. A., Cordones, I., Ammann, C., et al. 2021. ‘Immediate and after Effects of Transcranial Direct-Current Stimulation in the Mouse Primary Somatosensory Cortex’. Scientific Reports 11 (1): 3123.Google Scholar
Sandefur, Justin. 2016. ‘Internationally Comparable Mathematics Scores for Fourteen African Countries’. SSRN Electronic Journal. Center for Global Development Working Paper No. 444. https://doi.org/10.2139/ssrn.2893768.Google Scholar
Sanetti, L. M. Hagermoser, S. Charbonneau, A. Knight, , et al. 2020. ‘Treatment Fidelity Reporting in Intervention Outcome Studies in the School Psychology Literature from 2009 to 2016’. Psychology in the Schools 57 (6): 901–22.Google Scholar
Sanfilippo, J., Ness, M., Petscher, Y., et al. 2020. ‘Reintroducing Dyslexia: Early Identification and Implications for Pediatric Practice’. Pediatrics 146 (1). https://doi.org/10.1542/peds.2019-3046.Google Scholar
Sarnecka, B. W. 2014. ‘On the Relation between Grammatical Number and Cardinal Numbers in Development’. Frontiers in Psychology 5 (October): 1132.Google Scholar
Savage, R., Cornish, K., Manly, T., and Hollis, C.. 2006. ‘Cognitive Processes in Children’s Reading and Attention: The Role of Working Memory, Divided Attention, and Response Inhibition’. British Journal of Psychology 97 (Pt 3): 365–85.Google Scholar
Sax, L., and Kautz, K. J.. 2003. ‘Who First Suggests the Diagnosis of Attention-Deficit/hyperactivity Disorder?’ Annals of Family Medicine 1 (3): 171–4.Google Scholar
Scalise, N. R., Daubert, E. N., and Ramani, G. B.. 2020. ‘Benefits of Playing Numerical Card Games on Head Start Children’s Mathematical Skills’. Journal of Experimental Education 88 (2): 200–20.Google Scholar
Scarr, S., and McCartney, K.. 1983. ‘How People Make Their Own Environments: A Theory of Genotype → Environment Effects’. Child Development 54 (2): 424–35.Google Scholar
Scheirer, M. A., Shediac, M. C., and Cassady, C. E.. 1995. ‘Measuring the Implementation of Health Promotion Programs: The Case of the Breast and Cervical Cancer Program in Maryland’. Health Education Research 10 (1): 11–25. https://doi.org/10.1093/her/10.1.11.Google Scholar
Schiefele, U., Schaffner, E., Möller, J., and Wigfield, A.. 2012. ‘Dimensions of Reading Motivation and Their Relation to Reading Behavior and Competence’. Reading Research Quarterly 47 (4): 427–63.Google Scholar
Schmitt, S. A., John Geldhof, G., Purpura, D. J., Duncan, R., and McClelland, M. M.. 2017. ‘Examining the Relations between Executive Function, Math, and Literacy during the Transition to Kindergarten: A Multi-Analytic Approach’. Journal of Educational Psychology 109 (8): 1120–40.Google Scholar
Schneider, W. 2019. ‘Programme Zur Förderung Kognitiver Fähigkeiten in Vorschule Und Schule: Wie Effektiv Sind Sie, Und Wie Gut Sind Die Verfahren Praktisch Implementiert?’ Zeitschrift Für Pädagogische Psychologie 33 (1): 5–16. https://doi.org/10.1024/1010-0652/a000231.Google Scholar
Schneider, W., and Bullock, M.. 2009. ‘The Development of Reading and Spelling: Relevant Precursors, Developmental Changes, and Individual Differences’. In Schneider, and Bullock, . (eds.) Human Development from Early Childhood to Early Adulthood, 209–30. Psychology Press.Google Scholar
Schneider, W., Küspert, P., Roth, E., Visé, M., and Marx, H.. 1997. ‘Short- and Long-Term Effects of Training Phonological Awareness in Kindergarten: Evidence from Two German Studies’. Journal of Experimental Child Psychology 66 (3): 311–40. https://doi.org/10.1006/jecp.1997.2384.Google Scholar
Schneider, W., Roth, E., and Ennemoser, M.. 2000. ‘Training Phonological Skills and Letter Knowledge in Children at Risk for Dyslexia: A Comparison of Three Kindergarten Intervention Programs’. Journal of Educational Psychology 92 (2): 284–95. https://doi.org/10.1037/0022-0663.92.2.284.Google Scholar
Schneider, W., and Stengard, C.. 2000. Inventory of European Longitudinal Studies of Reading and Spelling: A COST Action A8 Project. Office for Official Publications of the European Communities.Google Scholar
Schrader, J., Hasselhorn, M., Hetfleisch, P., and Goeze, A.. 2020. ‘Stichwortbeitrag Implementationsforschung: Wie Wissenschaft Zu Verbesserungen Im Bildungssystem Beitragen Kann’. Zeitschrift Für Erziehungswissenschaft 23: 9–59. https://doi.org/10.1007/s11618-020-00927-z.CrossRefGoogle Scholar
Schroeder, P. A., Dresler, T., Bahnmueller, J., et al. 2017. ‘Cognitive Enhancement of Numerical and Arithmetic Capabilities: A Mini-Review of Available Transcranial Electric Stimulation Studies’. Journal of Cognitive Enhancement 1 (1), 39–47. https://doi.org/10.1007/s41465-016-0006-z.Google Scholar
Schulte, A., and Borich, G. D.. 1984. ‘Considerations in the Use of Difference Scores to Identify Learning-Disabled Children’. Journal of School Psychology 22 (4): 381–90.Google Scholar
Schulte-Körne, G. 2010. ‘Diagnostik Und Therapie Der Lese-Rechtschreib-Störung’. Deutsches Ärzteblatt 107 (41): 718–26.Google Scholar
Schwaighofer, M., Fischer, F., and Bühner, M.. 2015. ‘Does Working Memory Training Transfer? A Meta-Analysis Including Training Conditions as Moderators’. Educational Psychologist 50 (2): 138–66.Google Scholar
Schwartz, A. E., Hopkins, B. G., and Stiefel, L.. 2021. ‘The Effects of Special Education on the Academic Performance of Students with Learning Disabilities’. Journal of Policy Analysis and Management: [the Journal of the Association for Public Policy Analysis and Management] 40 (2): 480–520.Google Scholar
Schwering, S. C., and MacDonald, M. C.. 2020. ‘Verbal Working Memory as Emergent from Language Comprehension and Production’. Frontiers in Human Neuroscience 14 (March): 68.Google Scholar
Scruggs, T. E., Mastropieri, M. A., Berkeley, S., and Graetz, J. E.. 2010. ‘Do Special Education Interventions Improve Learning of Secondary Content? A Meta-Analysis’. Remedial and Special Education: RASE 31 (6): 437–49.Google Scholar
Segers, E., Damhuis, C. M. P., van de Sande, E., and Verhoeven, L.. 2016. ‘Role of Executive Functioning and Home Environment in Early Reading Development’. Learning and Individual Differences 49: 251–9. https://doi.org/10.1016/j.lindif.2016.07.004.Google Scholar
Seidenberg, M. 2018. Language at the Speed of Sight: How We Read, Why So Many Can’t, and What Can Be Done About It. Basic Books.Google Scholar
Seitzman, B. A., Gratton, C., Laumann, T. O., et al. 2019. ‘Trait-like Variants in Human Functional Brain Networks’. Proceedings of the National Academy of Sciences of the United States of America 116 (45): 22851–61.Google Scholar
Sella, F., Tressoldi, P., Lucangeli, D., and Zorzi, M.. 2016. ‘Training Numerical Skills with the Adaptive Videogame ‘The Number Race’: A Randomized Controlled Trial on Preschoolers’. Trends in Neuroscience and Education 5 (1): 20–9.Google Scholar
Sen, A, et al. 1979. ‘Equality of What’. The Tanner Lecture on Human Values 22. http://tannerlectures.utah.edu/_documents/a-to-z/s/sen80.pdf.Google Scholar
Sénéchal, M., and LeFevre, J.-A. 2002. ‘Parental Involvement in the Development of Children’s Reading Skill: A Five-Year Longitudinal Study’. Child Development 73 (2): 445–60.Google Scholar
Seymour, P. H. K., Aro, M, Erskine, J. M., in collaboration with COST Action A8 Network. 2003. ‘Foundation Literacy Acquisition in European Orthographies’. British Journal of Psychology 94 (2): 143–74. https://doi.org/10.1348/000712603321661859.CrossRefGoogle ScholarPubMed
Shakeshaft, N. G., Trzaskowski, M., McMillan, A., et al. 2013. ‘Strong Genetic Influence on a UK Nationwide Test of Educational Achievement at the End of Compulsory Education at Age 16’. PloS One 8 (12): e80341.Google Scholar
Shakespeare, T. 2013. Disability Rights and Wrongs Revisited. Routledge.CrossRefGoogle Scholar
Shankweiler, D., Mencl, W. E., Braze, D., et al. 2008. ‘Reading Differences and Brain: Cortical Integration of Speech and Print in Sentence Processing Varies with Reader Skill’. Developmental Neuropsychology 33 (6): 745–75.Google Scholar
Share, D. L. 1996. ‘Word Recognition and Spelling Processes in Specific Reading Disabled and Garden-Variety Poor Readers’. Dyslexia 2 (3): 167–74. https://doi.org/10.1002/(sici)1099-0909(199611)2:3<167::aid-dys167>3.0.co;2-o.Google Scholar
Share, D. L. 2008. ‘On the Anglocentricities of Current Reading Research and Practice: The Perils of Overreliance on an ‘Outlier’ Orthography’. Psychological Bulletin 134 (4): 584–615. https://doi.org/10.1037/0033-2909.134.4.584.Google Scholar
Share, D. L., Shany, M., and Lipka, O.. 2019. ‘Developmental Dyslexia in Hebrew’. In Verhoeven, L., Perfetti, C., & Pugh, K. (Eds.). Developmental Dyslexia across Languages and Writing Systems. Cambridge University Press, 152–75.Google Scholar
Share, D. L. 1995. ‘Phonological Recoding and Self-Teaching: Sine qua Non of Reading Acquisition’. Cognition 55 (2): 151–218; discussion 219–26.Google Scholar
Sharkey, P., and Elwert, F.. 2011. ‘The Legacy of Disadvantage: Multigenerational Neighborhood Effects on Cognitive Ability’. AJS: American Journal of Sociology 116 (6): 1934–81.Google Scholar
Shaywitz, S. E., Fletcher, J. M., Holahan, J. M., et al. 1999. ‘Persistence of Dyslexia: The Connecticut Longitudinal Study at Adolescence’. Pediatrics 104 (6): 1351–59.Google Scholar
Shaywitz, S. E., Shaywitz, B. A., Fulbright, R. K., et al. 2003. ‘Neural Systems for Compensation and Persistence: Young Adult Outcome of Childhood Reading Disability’. Biological Psychiatry 54 (1): P25–33. https://doi.org/10.1016/s0006-3223(02)01836-x.Google Scholar
Shaywitz, S., Shaywitz, B., Wietecha, L., et al. 2017. ‘Effect of Atomoxetine Treatment on Reading and Phonological Skills in Children with Dyslexia or Attention-Deficit/Hyperactivity Disorder and Comorbid Dyslexia in a Randomized, Placebo-Controlled Trial’. Journal of Child and Adolescent Psychopharmacology 27 (1): 19–28.Google Scholar
Shaywitz, S. E. 1998. ‘Dyslexia’. The New England Journal of Medicine 338 (5): 307–12.Google Scholar
Shaywitz, S. E., Escobar, M. D., Shaywitz, B. A., Fletcher, J. M., and Makuch, R.. 1992. ‘Evidence That Dyslexia May Represent the Lower Tail of a Normal Distribution of Reading Ability’. The New England Journal of Medicine 326 (3): 145–50.Google Scholar
Shaywitz, S. E., Shaywitz, B. A., Fletcher, J. M., and Escobar, M. D.. 1990. ‘Prevalence of Reading Disability in Boys and Girls. Results of the Connecticut Longitudinal Study’. JAMA: The Journal of the American Medical Association 264 (8): 998–1002.Google Scholar
Shifrer, D. 2018. ‘Clarifying the Social Roots of the Disproportionate Classification of Racial Minorities and Males with Learning Disabilities’. The Sociological Quarterly 59 (3): 384–406.Google Scholar
Shifrer, D., and Fish, R.. 2020. ‘A Multilevel Investigation into Contextual Reliability in the Designation of Cognitive Health Conditions among U.S. Children’. Society and Mental Health 10 (2): 180–97.Google Scholar
Shmueli, G. 2010. ‘To Explain or to Predict?’ Statistical Science 25 (3): 289–310.Google Scholar
Shu, H., Chen, X., Anderson, R. C., Wu, N., and Xuan, Y.. 2003. ‘Properties of School Chinese: Implications for Learning to Read’. Child Development 74 (1): 27–47.Google Scholar
Siegel, L. S., and Himel, N.. 1998. ‘Socioeconomic Status, Age and the Classification of Dyslexics and Poor Readers: The Dangers of Using IQ Scores in the Definition of Reading Disability’. Dyslexia 4 (2): 90–104.Google Scholar
Siegel, L. S., and Ryan, E. B.. 1989. ‘Subtypes of Developmental Dyslexia: The Influence of Definitional Variables’. Reading and Writing 1 (3): 257–87.Google Scholar
Siegel, L. S., and Smythe, I. S.. 2005. ‘Reflections on Research on Reading Disability with Special Attention to Gender Issues’. Journal of Learning Disabilities 38 (5): 473–77. https://doi.org/10.1177/00222194050380050901.Google Scholar
Siegel, L. S. 1992. ‘An Evaluation of the Discrepancy Definition of Dyslexia’. Journal of Learning Disabilities 25 (10): 618–29.Google Scholar
Siegler, R. S., and Booth, J. L.. 2004. ‘Development of Numerical Estimation in Young Children’. Child Development 75 (2): 428–44.Google Scholar
Siegler, R. S., and Braithwaite, D. W.. 2017. ‘Numerical Development’. Annual Review of Psychology 68 (January): 187–213.CrossRefGoogle ScholarPubMed
Siegler, R. S., and Lortie-Forgues, H.. 2014. ‘An Integrative Theory of Numerical Development’. Child Development Perspectives 8 (3): 144–50. https://doi.org/10.1111/cdep.12077.Google Scholar
Siegler, R. S., and Opfer, J. E.. 2003. ‘The Development of Numerical Estimation: Evidence for Multiple Representations of Numerical Quantity’. Psychological Science 14 (3): 237–43.Google Scholar
Siegler, R. S., and Ramani, G. B.. 2009. ‘Playing Linear Number Board Games – but Not Circular Ones – Improves Low-Income Preschoolers’ Numerical Understanding’. Journal of Educational Psychology 101 (3): 545–60.Google Scholar
Simanowski, S., and Krajewski, K.. 2019. ‘Specific Preschool Executive Functions Predict Unique Aspects of Mathematics Development: A 3-Year Longitudinal Study’. Child Development 90 (2): 544–61.Google Scholar
Simms, V., Clayton, S., Cragg, L., Gilmore, C., and Johnson, S.. 2016. ‘Explaining the Relationship between Number Line Estimation and Mathematical Achievement: The Role of Visuomotor Integration and Visuospatial Skills’. Journal of Experimental Child Psychology 145 (May): 22–33.Google Scholar
Simons, D. J., Boot, W. R., Charness, N, et al. 2016. ‘Do “Brain-Training” Programs Work?’ Psychological Science in the Public Interest: A Journal of the American Psychological Society 17 (3): 103–86.Google Scholar
Simonsmeier, B. A., Grabner, R. H., Hein, J., Krenz, U., and Schneider, M.. 2018. ‘Electrical Brain Stimulation (tES) Improves Learning More than Performance: A Meta-Analysis’. Neuroscience and Biobehavioral Reviews 84 (January): 171–81.Google Scholar
Simos, P. G., Kanatsouli, K, Fletcher, J. M., et al. 2008. ‘Aberrant Spatiotemporal Activation Profiles Associated with Math Difficulties in Children: A Magnetic Source Imaging Study’. Neuropsychology 22 (5): 571–84.Google Scholar
Simos, P. G., Breier, J. I., Fletcher, J. M., et al. 2001. ‘Age-Related Changes in Regional Brain Activation during Phonological Decoding and Printed Word Recognition’. Developmental Neuropsychology 19 (2): 191–210.Google Scholar
Simos, P. G., Fletcher, J. M., Bergman, E., et al. 2002. ‘Dyslexia-Specific Brain Activation Profile Becomes Normal Following Successful Remedial Training’. Neurology 58 (8): 1203–13.Google Scholar
Siok, W. T., Jia, F., Liu, C. Y., Perfetti, C. A., and Tan, L. H.. 2020. ‘A Lifespan fMRI Study of Neurodevelopment Associated with Reading Chinese’. Cerebral Cortex 30 (7): 4140–57.Google Scholar
Siok, W. T., Jin, Z., Fletcher, P., and Tan, L. H.. 2003. ‘Distinct Brain Regions Associated with Syllable and Phoneme’. Human Brain Mapping 18: 201–7. https://doi.org/10.1002/hbm.10094.Google Scholar
Siok, W. T., Spinks, J. A., Jin, Z., and Tan, L. H.. 2009. ‘Developmental Dyslexia Is Characterized by the Co-Existence of Visuospatial and Phonological Disorders in Chinese Children’. Current Biology 19 (1): PR890–R892. https://doi.org/10.1016/j.cub.2009.08.014.Google Scholar
Siok, W. T., and Fletcher, P.. 2001. ‘The Role of Phonological Awareness and Visual-Orthographic Skills in Chinese Reading Acquisition’. Developmental Psychology 37 (6): 886–99.Google Scholar
Siok, W. T., Niu, Z., Jin, Z., Perfetti, C. A., and Tan, L. H.. 2008. ‘A Structural-Functional Basis for Dyslexia in the Cortex of Chinese Readers’. Proceedings of the National Academy of Sciences 105 (14): 18391194. https://doi.org/10.1073/pnas.0801750105.Google Scholar
Sirin, Selcuk R. 2005. ‘Socioeconomic Status and Academic Achievement: A Meta-Analytic Review of Research’. Review of Educational Research 75 (3): 417–53. https://doi.org/10.3102/00346543075003417.Google Scholar
Skeide, M. A. (ed.) 2022. The Cambridge Handbook of Dyslexia and Dyscalculia. Cambridge University Press.Google Scholar
Skeide, M. A., Kirsten, H., Kraft, I., et al. 2015. ‘Genetic Dyslexia Risk Variant Is Related to Neural Connectivity Patterns Underlying Phonological Awareness in Children’. NeuroImage 118 (September): 414–21.Google Scholar
Skeide, M. A., Kraft, I., Müller, B., et al. 2016. ‘NRSN1associated Grey Matter Volume of the Visual Word Form Area Reveals Dyslexia before School’. Brain 139 (10): 2792–803. https://doi.org/10.1093/brain/aww153.Google Scholar
Skiba, R. J., Poloni-Staudinger, L., Simmons, A. B., Feggins-Azziz, L. R., and Chung, C.-G.. 2005. ‘Unproven Links: Can Poverty Explain Ethnic Disproportionality in Special Education?’ The Journal of Special Education 39 (3): 130–44.Google Scholar
Skwarchuk, S.-L., Sowinski, C., and LeFevre, J.-A.. 2014. ‘Formal and Informal Home Learning Activities in Relation to Children’s Early Numeracy and Literacy Skills: The Development of a Home Numeracy Model’. Journal of Experimental Child Psychology 121 (May): 63–84.Google Scholar
Sleeter, C. 2010. ‘Why Is There Learning Disabilities? A Critical Analysis of the Birth of the Field in Its Social Context’. Disability Studies Quarterly: DSQ 30 (2). https://doi.org/10.18061/dsq.v30i2.1261.Google Scholar
Sniekers, S., Stringer, S., Watanabe, K, et al. 2017. ‘Genome-Wide Association Meta-Analysis of 78,308 Individuals Identifies New Loci and Genes Influencing Human Intelligence’. Nature Genetics 49 (7): 1107–12.Google Scholar
Snowling, M., and Hulme, C.. 1989. ‘A Longitudinal Case Study of Developmental Phonological Dyslexia’. Cognitive Neuropsychology 6 (4): 379–401. https://doi.org/10.1080/02643298908253289.CrossRefGoogle Scholar
Snowling, M. J. 2019. Dyslexia. Oxford University Press.Google Scholar
Snowling, M. J., Gallagher, A., and Frith, U.. 2003. ‘Family Risk of Dyslexia Is Continuous: Individual Differences in the Precursors of Reading Skill’. Child Development 74 (2): 358–73.Google Scholar
Snowling, M. J., Hayiou-Thomas, M. E., Nash, H. M., and Hulme, C.. 2020. ‘Dyslexia and Developmental Language Disorder: Comorbid Disorders with Distinct Effects on Reading Comprehension’. Journal of Child Psychology and Psychiatry, and Allied Disciplines 61 (6): 672–80.Google Scholar
Snowling, M. J., and Hulme, C.. 2011. ‘Evidence-Based Interventions for Reading and Language Difficulties: Creating a Virtuous Circle’. British Journal of Educational Psychology 81 (1): 1–23. https://doi.org/10.1111/j.2044-8279.2010.02014.x.Google Scholar
Snowling, M. J., Lervåg, A., Nash, H. M., and Hulme, C.. 2019. ‘Longitudinal Relationships between Speech Perception, Phonological Skills and Reading in Children at High-Risk of Dyslexia’. Developmental Science 22 (1): e12723.Google Scholar
Sokolowski, Andrzej. 2018. Scientific Inquiry in Mathematics – Theory and Practice: A STEM Perspective. Springer.Google Scholar
Sokolowski, H. M., and Ansari, D. (2018). Understanding the Effects of Education through the Lens of Biology’. NPJ Science of Learning 3 (1) (October): 17. https://doi.org/10.1038/s41539-018-0032-y.Google Scholar
Sokolowski, H. M., Sokolowski, H. M., Fias, W., Ononye, C. B., and Ansari, D.. 2017. ‘Are Numbers Grounded in a General Magnitude Processing System? A Functional Neuroimaging Meta-Analysis’. Neuropsychologia 105: 50–69. https://doi.org/10.1016/j.neuropsychologia.2017.01.019.Google Scholar
Sokolowski, M. B., and Wahlsten, D.. 2001. ‘Gene-Environment Interaction and Complex Behavior’. In Chin, H. R and Moldin, S. O (eds.), Methods in Genomic Neuroscience, 3–28. CRC Press.Google Scholar
Solan, H. A., Shelley-Tremblay, J., Ficarra, A., Silverman, M., and Larson, S.. 2003. ‘Effect of Attention Therapy on Reading Comprehension’. Journal of Learning Disabilities 36 (6): 556–63.Google Scholar
Solar Energy Research Inst., Golden, CO (USA). 1980. ‘Studying the Implementation of Public Programs’. https://doi.org/10.2172/5487716.Google Scholar
Solis, M., Ciullo, S., Vaughn, S., et al. 2012. ‘Reading Comprehension Interventions for Middle School Students With Learning Disabilities: A Synthesis of 30 Years of Research’. Journal of Learning Disabilities 45 (4): 327–40.Google Scholar
Soltanlou, M., Artemenko, C., Dresler, T, et al. 2019. ‘Math Anxiety in Combination With Low Visuospatial Memory Impairs Math Learning in Children’. Frontiers in Psychology 10 (January): 89.Google Scholar
Sommer, I. E. C. 2004. ‘Do Women Really Have More Bilateral Language Representation than Men? A Meta-Analysis of Functional Imaging Studies’. Brain 127 (8): 1845–52. https://doi.org/10.1093/brain/awh207.CrossRefGoogle Scholar
Sommer, I. E., Aleman, A., Somers, M., Boks, M. P., and Kahn, R. S.. 2008. ‘Sex Differences in Handedness, Asymmetry of the Planum Temporale and Functional Language Lateralization’. Brain Research 1206 (April): 76–88.Google Scholar
Song, S., Zilverstand, A., Gui, W., Li, H.-J., and Zhou, X.. 2019a. ‘Effects of Single-Session versus Multi-Session Non-Invasive Brain Stimulation on Craving and Consumption in Individuals with Drug Addiction, Eating Disorders or Obesity: A Meta-Analysis’. Brain Stimulation 12 (3): P606–18. https://doi.org/10.1016/j.brs.2018.12.975.Google Scholar
Song, S, Zhang, Y, Shu, H, Su, M and McBride, C (2020) ‘Universal and Specific Predictors of Chinese Children With Dyslexia – Exploring the Cognitive Deficits and Subtypes’. Front. Psychol. 10:2904. doi: 10.3389/fpsyg.2019.02904.CrossRefGoogle Scholar
Spaepen, E., Gunderson, E. A., Gibson, D., Goldin-Meadow, S., and Levine, S. C.. 2018. ‘Meaning before Order: Cardinal Principle Knowledge Predicts Improvement in Understanding the Successor Principle and Exact Ordering’. Cognition 180 (November): 59–81.Google Scholar
Spencer, M., Wagner, R. K., Schatschneider, C., et al. 2014. ‘Incorporating RTI in a Hybrid Model of Reading Disability’. Learning Disability Quarterly: Journal of the Division for Children with Learning Disabilities 37 (3): 161–71.CrossRefGoogle Scholar
Sprick, J. T., Bouck, E. C., Berg, T. R., and Coughlin, C.. 2020. ‘Attendance and Specific Learning Disability Identification: A Survey of Practicing School Psychologists’. Learning Disabilities Research & Practice: A Publication of the Division for Learning Disabilities, Council for Exceptional Children 35 (3): 139–49.Google Scholar
Squires, K. E., and Wolter, J. A.. 2016. ‘The Effects of Orthographic Pattern Intervention on Spelling Performance of Students With Reading Disabilities: A Best Evidence Synthesis’. Remedial and Special Education: RASE 37 (6): 357–69.Google Scholar
Stanovich, K. E. 1994. ‘Annotation: Does Dyslexia Exist?’ Journal of Child Psychology and Psychiatry, and Allied Disciplines 35 (4): 579–95.Google Scholar
Stanovich, K. E. 1991. ‘Discrepancy Definitions of Reading Disability: Has Intelligence Led Us Astray?’ Reading Research Quarterly 26 (1): 7–29.Google Scholar
Stanovich, K. E. 2005. ‘The Future of a Mistake: Will Discrepancy Measurement Continue to Make the Learning Disabilities Field a Pseudoscience?’ Learning Disability Quarterly: Journal of the Division for Children with Learning Disabilities 28 (2): 103–6.Google Scholar
Steinbrink, C., Ackermann, H., Lachmann, T., and Riecker, A.. 2009. ‘Contribution of the Anterior Insula to Temporal Auditory Processing Deficits in Developmental Dyslexia’. Human Brain Mapping 30 (8): 2401–11.Google Scholar
Steinbrink, C., and Lachmann, T.. 2014. Lese-Rechtschreibstörung. Springer. https://doi.org/10.1007/978-3-642-41842-6.Google Scholar
Steinbrink, C., Schwanda, S., Klatte, M., and Lachmann, T.. 2010. ‘Sagen Wahrnehmungsleistungen Zu Beginn Der Schulzeit Den Lese-Rechtschreiberfolg in Klasse 1 Und 2 Voraus?’ Zeitschrift Fur Entwicklungspsychologie Und Padagogische Psychologie 42 (4): 188–200.Google Scholar
Stein, J. F., Richardson, A. J., and Fowler, M. S.. 2000. ‘Monocular Occlusion Can Improve Binocular Control and Reading in Dyslexics’. Brain: A Journal of Neurology 123 (Pt 1) (January): 164–70.Google Scholar
Stein, J. 2018. ‘The Magnocellular Theory of Developmental Dyslexia’. Literacy Studies 16. https://doi.org/10.1007/978-3-319-90805-2_6.Google Scholar
Stein, J. F. 2018. ‘Does Dyslexia Exist?’ Language, Cognition and Neuroscience 33 (3): 313–20.Google Scholar
Stevens, E. A., Rodgers, M. A., and Powell, S. R.. 2018. ‘Mathematics Interventions for Upper Elementary and Secondary Students: A Meta-Analysis of Research’. Remedial and Special Education: RASE 39 (6): 327–40.Google Scholar
Steyer, R., Majcen, A.-M., Schwenkmezger, P., and Buchner, A.. 1989. ‘A Latent State-Trait Anxiety Model and Its Application to Determine Consistency and Specificity Coefficients’. Anxiety Research 1 (4): 281–99.Google Scholar
Storch, S. A., and Whitehurst, G. J.. 2002. ‘Oral Language and Code-Related Precursors to Reading: Evidence from a Longitudinal Structural Model’. Developmental Psychology 38 (6): 934–47. https://doi.org/10.1037/0012-1649.38.6.934.Google Scholar
Storebø, O. J., Stoffers-Winterling, J. M., Völlm, B. A., et al. 2018. ‘Psychological Therapies for People with Borderline Personality Disorder’. The Cochrane Library 2: CD012955, February. https://doi.org/10.1002/14651858.cd012955.Google Scholar
Strand, S., and Lindsay, G.. 2009. ‘Evidence of Ethnic Disproportionality in Special Education in an English Population’. The Journal of Special Education 43 (3): 174–90.Google Scholar
Stuebing, K. K., Fletcher, J. M., LeDoux, J. M., et al. 2002. ‘Validity of IQ-Discrepancy Classifications of Reading Disabilities: A Meta-Analysis’. American Educational Research Journal 39 (2): 469–518. https://doi.org/10.3102/00028312039002469.Google Scholar
Stutz, F., Schaffner, E., and Schiefele, U.. 2016. ‘Relations among Reading Motivation, Reading Amount, and Reading Comprehension in the Early Elementary Grades’. Learning and Individual Differences 45: 101–13. https://doi.org/10.1016/j.lindif.2015.11.022.Google Scholar
Suggate, S. P. 2016. ‘A Meta-Analysis of the Long-Term Effects of Phonemic Awareness, Phonics, Fluency, and Reading Comprehension Interventions’. Journal of Learning Disabilities 49 (1): 77–96. https://doi.org/10.1177/0022219414528540.Google Scholar
Sun, Z., Zou, L., Zhang, J., et al. 2013. ‘Prevalence and Associated Risk Factors of Dyslexic Children in a Middle-Sized City of China: A Cross-Sectional Study’. PloS One 8 (2): e56688.Google Scholar
Swanson, H. 2015. ‘Cognitive Strategy Interventions Improve Word Problem Solving and Working Memory in Children with Math Disabilities’. Frontiers in Psychology 6: 1099.Google Scholar
Swanson, H. L. 1999. ‘Reading Research for Students with LD: A Meta-Analysis of Intervention Outcomes’. Journal of Learning Disabilities 32 (6): 504–32.Google Scholar
Swanson, H. L. 2011. ‘Working Memory, Attention, and Mathematical Problem Solving: A Longitudinal Study of Elementary School Children’. Journal of Educational Psychology 103 (4): 821–37.Google Scholar
Swanson, H. L., Moran, A., Lussier, C., and Fung, W.. 2014. ‘The Effect of Explicit and Direct Generative Strategy Training and Working Memory on Word Problem-Solving Accuracy in Children at Risk for Math Difficulties’. Learning Disability Quarterly: Journal of the Division for Children with Learning Disabilities 37 (2): 111–23.Google Scholar
Takala, M., Silfver, E., Karlsson, Y., and Saarinen, M.. 2020. ‘Supporting Pupils in Finnish and Swedish Schools – Teachers’ Views’. Scandinavian Journal of Educational Research 64 (3): 313–32. https://doi.org/10.1080/00313831.2018.1541820.Google Scholar
‘TALIS 2018 Results (volume I): Teachers and School Leaders as Lifelong Learners’. n.d. Accessed July 29, 2021. https://www.oecd-ilibrary.org/education/talis-2018-results-volume-i_1d0bc92a-en.Google Scholar
Tallal, Paula. 1980. ‘Auditory Temporal Perception, Phonics, and Reading Disabilities in Children’. Brain and Language 9 (2): 182–98. https://doi.org/10.1016/0093-934x(80)90139-x.Google Scholar
Tan, L. H., Spinks, J. A., Eden, G. F., Perfetti, C. A., and Siok, W. T.. 2005. ‘Reading Depends on Writing, in Chinese’. Proceedings of the National Academy of Sciences 102 (24). https://doi.org/10.1073/pnas.0503523102.Google Scholar
Tan, L. H., Laird, A. R., Li, K., and Fox, P. T.. 2005. ‘Neuroanatomical Correlates of Phonological Processing of Chinese Characters and Alphabetic Words: A Meta-Analysis’. Human Brain Mapping 25 (1): 83–91.Google Scholar
Tan, L. H., Spinks, J. A., Feng, C.-M., et al. 2003. ‘Neural Systems of Second Language Reading Are Shaped by Native Language’. Human Brain Mapping 18: 158–66. https://doi.org/10.1002/hbm.10089.Google Scholar
Tarone, E., and Bigelow, M.. 2005. ‘Impact of Literacy on Oral Language Processing: Implications for Second Language Acquisition Research’. Annual Review of Applied Linguistics 25: 77–97. https://doi.org/10.1017/s0267190505000048.Google Scholar
Temple, E., Poldrack, R. A., Salidis, J., et al. 2001. ‘Disrupted Neural Responses to Phonological and Orthographic Processing in Dyslexic Children: An fMRI Study’. Neuroreport 12 (2): 299–307. https://doi.org/10.1097/00001756-200102120-00024.Google Scholar
Tenenbaum, H. R., and Ruck, M. D.. 2007. ‘Are Teachers’ Expectations Different for Racial Minority than for European American Students? A Meta-Analysis’. Journal of Educational Psychology 99 (2): 253–73.Google Scholar
Terney, D., Chaieb, L., Moliadze, V., Antal, A., and Paulus, W.. 2008. ‘Increasing Human Brain Excitability by Transcranial High-Frequency Random Noise Stimulation’. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 28 (52): 14147–55.CrossRefGoogle ScholarPubMed
Thomas Boyce, W., Sokolowski, M. B., and Robinson, G. E.. 2020. ‘Genes and Environments, Development and Time’. Proceedings of the National Academy of Sciences of the United States of America 117 (38): 23235–41.Google Scholar
TIMSS, and PIRLS International Study Center at Boston College. n.d. ‘TIMSS 2019 International Results in Mathematics and Science’. Accessed July 29, 2021. https://timssandpirls.bc.edu/timss2019/.Google Scholar
Tobia, V., and Marzocchi, G. M.. 2014. ‘Predictors of Reading Fluency in Italian Orthography: Evidence from a Cross-Sectional Study of Primary School Students’. Child Neuropsychology: A Journal on Normal and Abnormal Development in Childhood and Adolescence 20 (4): 449–69.Google Scholar
Toh, T. L., and Kaur, B.. 2019. ‘Low Attainers and Learning of Mathematics’. In Toh, T., Kaur, B., and Tay, E. (eds) Mathematics Education in Singapore. Mathematics Education – An Asian Perspective. Springer. https://doi.org/10.1007/978-981-13-3573-0_13.Google Scholar
Topping, K. J., Miller, D., Murray, P., Henderson, S., Fortuna, C., and Conlin, N.. 2011. ‘Outcomes in a Randomised Controlled Trial of Mathematics Tutoring’. Educational Research 53 (1): 51–63.Google Scholar
Torgesen, J. K. 2000. ‘Individual Differences in Response to Early Interventions in Reading: The Lingering Problem of Treatment Resisters’. Learning Disabilities Research & Practice: A Publication of the Division for Learning Disabilities, Council for Exceptional Children 15 (2000): 55–64.Google Scholar
Törmänen, M. R. K., and Takala, M.. 2009. ‘Auditory Processing in Developmental Dyslexia: An Exploratory Study of an Auditory and Visual Matching Training Program with Swedish Children with Developmental Dyslexia’. Scandinavian Journal of Psychology 50 (3): 277–85.Google Scholar
Torppa, M., Georgiou, K., Lerkkanen, M.-K, et al. 2016. ‘Examining the Simple View of Reading in a Transparent Orthography: A Longitudinal Study From Kindergarten to Grade 3’. Merrill-Palmer Quarterly 62 (2): 179–206. https://doi.org/10.13110/merrpalmquar1982.62.2.0179.Google Scholar
Toste, J. R., Compton, D. L., Fuchs, D., et al. 2014. ‘Understanding Unresponsiveness to Tier 2 Reading Intervention: Exploring the Classification and Profiles of Adequate and Inadequate Responders in First Grade’. Learning Disability Quarterly: Journal of the Division for Children with Learning Disabilities 37 (4): 192–203.Google Scholar
Toth, G., and Siegel, L. S.. 2020. ‘A Critical Evaluation of the IQ-Achievement Discrepancy Based Definition of Dyslexia’. Current Directions in Dyslexia Research. Garland Science. https://doi.org/10.1201/9781003077411-4.Google Scholar
Tucker-Drob, E. M., and Bates, T. C.. 2016. ‘Large Cross-National Differences in Gene × Socioeconomic Status Interaction on Intelligence’. Psychological Science 27 (2): 138–49.Google Scholar
Turkeltaub, P. E., Benson, J., Hamilton, R. H., et al. 2012. ‘Left Lateralizing Transcranial Direct Current Stimulation Improves Reading Efficiency’. Brain Stimulation 5 (3): 201–7.Google Scholar
Turkeltaub, P. E., Gareau, L., Flowers, D. L., Zeffiro, T. A., and Eden, G. F.. 2003a. ‘Development of Neural Mechanisms for Reading’. Nature Neuroscience 6: 767–73. https://doi.org/10.1038/nn1065.Google Scholar
Turkeltaub, P. E., Gareau, L., Flowers, D. L., Zeffiro, T. A., and Eden, G. F. 2003b. ‘Development of Neural Mechanisms for Reading’. Nature Neuroscience 6 (7): 767–73.CrossRefGoogle ScholarPubMed
Tzeng, Y.-L., Hsu, C.-H., Lin, W.-H., and Lee, C.-Y.. 2018. ‘Impaired Orthographic Processing in Chinese Dyslexic Children: Evidence From the Lexicality Effect on N400’. Scientific Studies of Reading: The Official Journal of the Society for the Scientific Study of Reading 22 (1): 85–100.Google Scholar
Ulferts, H., Wolf, K. M., and Anders, Y.. 2019. ‘Impact of Process Quality in Early Childhood Education and Care on Academic Outcomes: Longitudinal Meta‐Analysis’. Child Development 90: 1474–89. https://doi.org/10.1111/cdev.13296.Google Scholar
Uno, A., Wydell, T. N., Haruhara, N., Kaneko, M., and Shinya, N.. 2009. ‘Relationship between Reading/writing Skills and Cognitive Abilities among Japanese Primary-School Children: Normal Readers versus Poor Readers (Dyslexics)’. Reading and Writing 22 (7): 755–89.Google Scholar
United Nations, and United Nations (UN). 2009. ‘Convention on the Rights of Persons with Disabilities’. Jahrbuch Für Wissenschaft Und Ethik 14 (1). https://doi.org/10.1515/9783110208856.203.Google Scholar
‘UQ eSpace’. n.d. Accessed July 29, 2021. https://espace.library.uq.edu.au/view/UQ: 733076.Google Scholar
Usami, S., Murayama, K., and Hamaker, E. L.. 2019. ‘A Unified Framework of Longitudinal Models to Examine Reciprocal Relations’. Psychological Methods 24 (5): 637–57. https://dx.doi.org/10.1037/met0000210.Google Scholar
US Department of Education, Office of Special Education, and Office of Special Education Programs Rehabilitative Services. 2020. ‘41st Annual Report to Congress on the Implementation of the Individuals with Disabilities Education Act, 2019’. Education Publications Center Washington, DC.Google Scholar
Uttal, D. H., and Cohen, C. A.. 2012. ‘Chapter Four – Spatial Thinking and STEM Education: When, Why, and How?’ In Psychology of Learning and Motivation, edited by Ross, Brian H., 57:147–81. Academic Press.Google Scholar
Uttal, D. H., Meadow, N. G., Tipton, E., et al. 2013. ‘The Malleability of Spatial Skills: A Meta-Analysis of Training Studies’. Psychological Bulletin 139 (2): 352–402.Google Scholar
Vaessen, A., Bertrand, D., Tóth, D., et al. 2010. ‘Cognitive Development of Fluent Word Reading Does Not Qualitatively Differ between Transparent and Opaque Orthographies’. Journal of Educational Psychology 102 (4): 827–42. https://doi.org/10.1037/a0019465.Google Scholar
Vágvölgyi, R., Bergström, K., Bulajić, A., et al. 2021. ‘Functional Illiteracy and Developmental Dyslexia: Looking for Common Roots. A Systematic Review’. Journal of Cultural Cognitive Science 5: 159–79. https://doi.org/10.1007/s41809-021-00074-9.Google Scholar
Vágvölgyi, R., Coldea, A., Dresler, T., Schrader, J., and Nuerk, H.-C.. 2016. ‘A Review about Functional Illiteracy: Definition, Cognitive, Linguistic, and Numerical Aspects’. Frontiers in Psychology 7 (November): 1617.Google Scholar
Valdois, Sylviane, Peyrin, Carole, Lassus-Sangosse, Delphine, et al. 2014. ‘Dyslexia in a French–Spanish Bilingual Girl: Behavioural and Neural Modulations Following a Visual Attention Span Intervention’. Cortex 53 (April): 120–45. https://doi.org/10.1016/j.cortex.2013.11.006.Google Scholar
Van den Broeck, W. 2002. ‘The Misconception of the Regression-Based Discrepancy Operationalization in the Definition and Research of Learning Disabilities’. Journal of Learning Disabilities 35 (3): 194–204.Google Scholar
Van Luit, J. E. H., and Schopman, E. A. M.. 2000. ‘Improving Early Numeracy of Young Children with Special Educational Needs’. Remedial and Special Education: RASE 21 (1): 27–40.Google Scholar
‘Vanuatu Inclusive Education (IE) Policy / Republic of Vanuatu, Ministry of Education’. 2011. Accessed July 29, 2021. https://education.gov.vu/docs/policies/Vanuatu%20Inclusive%20Education%20Policy_2011.pdf.Google Scholar
VanVoorhis, C. R. W., Morgan, B. L., and Others. 2007. ‘Understanding Power and Rules of Thumb for Determining Sample Sizes’. Tutorials in Quantitative Methods for Psychology 3 (2): 43–50.Google Scholar
Vaughn, S., and Fuchs, L. S.. 2003. ‘Redefining Learning Disabilities as Inadequate Response to Instruction: The Promise and Potential Problems’. Learning Disabilities Research and Practice 18 (3): 137–46. https://doi.org/10.1111/1540-5826.00070.Google Scholar
Veenstra, R., Lindenberg, S., Tinga, F., and Ormel, J.. 2010. ‘Truancy in Late Elementary and Early Secondary Education: The Influence of Social Bonds and Self-Control – the TRAILS Study’. International Journal of Behavioral Development 34 (4): 302–10. https://doi.org/10.1177/0165025409347987.Google Scholar
Ventura, P., Pattamadilok, C., Fernandes, T., et al. 2008. ‘Schooling in Western Culture Promotes Context-Free Processing’. Journal of Experimental Child Psychology 100 (2): 79–88.Google Scholar
Verdine, B. N., Golinkoff, R. M., Hirsh-Pasek, K., and Newcombe, N. S.. 2017. ‘Spatial Skills, Their Development, and Their Links to Mathematics’. Monographs of the Society for Research in Child Development 82 (1): 7–30.Google Scholar
Verhoeven, L., and Perfetti, C.. 2017. Learning to Read across Languages and Writing Systems. Cambridge University Press.Google Scholar
Verhoeven, L., Perfetti, C., Pugh, K., et al. 2019. Developmental Dyslexia across Languages and Writing Systems. Cambridge University Press.Google Scholar
Verpalen, A., Van de Vijver, F., and Backus, A.. 2018. ‘Bias in Dyslexia Screening in a Dutch Multicultural Population’. Annals of Dyslexia 68 (1): 43–68.Google Scholar
Visscher, P. M., Brown, M. A., McCarthy, M. I., and Yang, J.. 2012. ‘Five Years of GWAS Discovery’. American Journal of Human Genetics 90 (1): 7–24.Google Scholar
Visser, L., Kalmar, J., Linkersdörfer, J., et al. 2020. ‘Comorbidities between Specific Learning Disorders and Psychopathology in Elementary School Children in Germany’. Frontiers in Psychiatry. https://doi.org/10.3389/fpsyt.2020.00292.Google Scholar
Viterbori, P., Traverso, L., and Usai, M. C. 2017. ‘The Role of Executive Function in Arithmetic Problem-Solving Processes: A Study of Third Graders’. Journal of Cognition and Development: Official Journal of the Cognitive Development Society 18 (5): 595–616.Google Scholar
Viterbori, P., Usai, M. C., Traverso, L., and De Franchis, V.. 2015. ‘How Preschool Executive Functioning Predicts Several Aspects of Math Achievement in Grades 1 and 3: A Longitudinal Study’. Journal of Experimental Child Psychology 140 (December): 38–55.Google Scholar
Vogel, S. A. 1990. ‘Gender Differences in Intelligence, Language, Visual-Motor Abilities, and Academic Achievement in Students with Learning Disabilities’. Journal of Learning Disabilities 23 (1): 44–52. https://doi.org/10.1177/002221949002300111.Google Scholar
Volkmer, S., Galuschka, K., and Schulte-Körne, G.. 2019. ‘Early Identification and Intervention for Children with Initial Signs of Reading Deficits – A Blinded Randomized Controlled Trial’. Learning and Instruction 59 (February): 1–12.Google Scholar
Voss, S., Blumenthal, Y., Mahlau, K., et al. 2016. Der Response-to-Intervention-Ansatz in der Praxis: Evaluationsergebnisse zum Rügener Inklusionsmodell. Waxmann Verlag GmbH.Google Scholar
Wagner, J. B., and Johnson, S. C.. 2011. ‘An Association between Understanding Cardinality and Analog Magnitude Representations in Preschoolers’. Cognition 119 (1): 10–22.Google Scholar
Wagner, R. K., and Torgesen, J. K.. 1987. ‘The Nature of Phonological Processing and Its Causal Role in the Acquisition of Reading Skills’. Psychological Bulletin 101 (2): 192–212. https://doi.org/10.1037/0033-2909.101.2.192.Google Scholar
Wagner, R. K., Torgesen, J. K., and Rashotte, C. A.. 1994. ‘Development of Reading-Related Phonological Processing Abilities: New Evidence of Bidirectional Causality from a Latent Variable Longitudinal Study’. Developmental Psychology 30 (1): 73–87. https://doi.org/10.1037/0012-1649.30.1.73.Google Scholar
Wai, J., Lubinski, D., and Benbow, C. P.. 2009. ‘Spatial Ability for STEM Domains: Aligning over 50 Years of Cumulative Psychological Knowledge Solidifies Its Importance’. Journal of Educational Psychology 101 (4): 817–35.Google Scholar
Wallentin, M. 2009. ‘Putative Sex Differences in Verbal Abilities and Language Cortex: A Critical Review’. Brain and Language 108 (3): 175–83. https://doi.org/10.1016/j.bandl.2008.07.001.Google Scholar
Walley, A. C., Metsala, J. L., and Garlock, V. M.. 2003. ‘Spoken Vocabulary Growth: Its Role in the Development of Phoneme Awareness and Early Reading Ability’. Reading and Writing 16 (1): 5–20.Google Scholar
Wang, E., Qin, S., Chang, M., and Zhu, X.. 2015. ‘Digital Memory Encoding in Chinese Dyscalculia: An Event-Related Potential Study’. Research in Developmental Disabilities 36C (January): 142–49.Google Scholar
Washington, J. A., Compton, D. L., and McCardle, P.. 2020. Dyslexia: Revisiting Etiology, Diagnosis, Treatment, and Policy. Paul H. Brookes Publishing Company.Google Scholar
Watts, T. W., Duncan, G. J., Siegler, R. S., and Davis-Kean, P. E.. 2014. ‘What’s Past Is Prologue: Relations between Early Mathematics Knowledge and High School Achievement’. Educational Researcher 43 (7): 352–60.Google Scholar
Webb, N. M., Nemer, K. M., and Ing, M.. 2006. ‘Small-Group Reflections: Parallels between Teacher Discourse and Student Behavior in Peer-Directed Groups’. Journal of the Learning Sciences 15 (1): 63–119.Google Scholar
Weber, J., Marx, P., and Schneider, W.. 2007. ‘Die Prävention von Lese-Rechtschreibschwierigkeiten’. Zeitschrift Für Pädagogische Psychologie 21 (1): 1664–2910. https://doi.org/10.1024/1010-0652.21.1.65.Google Scholar
Wellesley College: Center for Research on Women. 1992. How Schools Shortchange Girls: The AAUW Report: A Study of Major Findings on Girls and Education. AAUW Educational Foundation. https://wcwonline.org/images/pdf/how-schools-shortchange-girls-executive_summary.pdf.Google Scholar
Wendt, H., Bos, W., Selter, C., et al. 2016. TIMSS 2015: mathematische und naturwissenschaftliche Kompetenzen von Grundschulkindern in Deutschland im internationalen Vergleich. Waxmann.Google Scholar
Wernicke, C. 1874. Der aphasische Symptomencomplex: eine psychologische Studie auf anatomischer Basis. Cohn & Weigert.Google Scholar
Werning, R., Löser, J. M., and Urban, M.. 2008. ‘Cultural and Social Diversity: An Analysis of Minority Groups in German Schools’. The Journal of Special Education 42 (1): 47–54.Google Scholar
Wheldall, K., and Limbrick, L.. 2010. ‘Do More Boys Than Girls Have Reading Problems?’ Journal of Learning Disabilities 43 (5): 418–29. https://doi.org/10.1177/0022219409355477.Google Scholar
White, B. 2007. ‘Are Girls Better Readers than Boys? Which Boys? Which Girls?’ Canadian Journal of Education / Revue Canadienne de L’éducation 30 (2): 554–81. https://doi.org/10.2307/20466650.Google Scholar
Whitehurst, G. J., and Lonigan, C. J.. 1998. ‘Child Development and Emergent Literacy’. Child Development 69 (3): 848–72.Google Scholar
White, I. R., Carpenter, J., and Horton, N. J.. 2012. ‘Including All Individuals Is Not Enough: Lessons for Intention-to-Treat Analysis’. Clinical Trials 9 (4): 396–407.Google Scholar
Whitley, J., and Hollweck, T.. 2020. ‘Inclusion and Equity in Education: Current Policy Reform in Nova Scotia, Canada’. Prospects, September, 1–16.Google Scholar
Willmes, K., Klein, E., and Nuerk, H.-C.. 2013. ‘Akalkulie’. In Funktionelle MRT in Psychiatrie Und Neurologie, edited by Schneider, F. and Fink, G. R., 577–86. Springer Berlin Heidelberg.Google Scholar
Willms, J. L., Shapiro, K. A., Peelen, M. V., et al. 2011. ‘Language-Invariant Verb Processing Regions in Spanish–English Bilinguals’. NeuroImage 57 (1): 251–61. https://doi.org/10.1016/j.neuroimage.2011.04.021.Google Scholar
Wilsher, C. R., and Taylor, E. A.. 1994. ‘Piracetam in Developmental Reading Disorders: A Review’. European Child & Adolescent Psychiatry 3 (2): 59–71.Google Scholar
Wilsher, C. R., Bennett, D., Chase, C. H., et al. 1987. ‘Piracetam and Dyslexia: Effects on Reading Tests’. Journal of Clinical Psychopharmacology 7 (4): 230–7.Google Scholar
Wilson, A. J., Revkin, S. K., Cohen, D., Cohen, L., and Dehaene, S.. 2006. ‘An Open Trial Assessment of ‘The Number Race’, an Adaptive Computer Game for Remediation of Dyscalculia’. Behavioral and Brain Functions: BBF 2 (1): 20.Google Scholar
Wimmer, H., and Mayringer, H.. 2002. ‘Dysfluent Reading in the Absence of Spelling Difficulties: A Specific Disability in Regular Orthographies’. Journal of Educational Psychology 94 (2): 272–7. https://doi.org/10.1037/0022-0663.94.2.272.Google Scholar
Wimmer, H., Mayringer, H., and Landerl, K.. 2000. ‘The Double-Deficit Hypothesis and Difficulties in Learning to Read a Regular Orthography’. Journal of Educational Psychology 94 (4): 668–80. https://doi.org/10.1037/0022-0663.92.4.668.Google Scholar
Wimmer, H., Landerl, K., Linortner, R., and Hummer, P.. 1991. ‘The Relationship of Phonemic Awareness to Reading Acquisition: More Consequence than Precondition but Still Important’. Cognition 40 (3): 219–49.Google Scholar
Witkowski, M., Garcia-Cossio, E., Chander, B. S., et al. 2016. ‘Mapping Entrained Brain Oscillations during Transcranial Alternating Current Stimulation (tACS)’. NeuroImage 140 (October): 89–98.Google Scholar
Wolf, K. M., Schroeders, U., and Kriegbaum, K.. 2016. ‘Metaanalyse Zur Wirksamkeit Einer Förderung Der Phonologischen Bewusstheit in Der Deutschen Sprache’. Zeitschrift Für Pädagogische Psychologie 30 (1): 1664–2910. https://doi.org/10.1024/1010-0652/a000165.Google Scholar
Wong, A. C.-.N., Bukach, C. M., Hsiao, J., et al. 2012. ‘Holistic Processing as a Hallmark of Perceptual Expertise for Nonface Categories Including Chinese Characters’. Journal of Vision 12 (7). https://doi.org/10.1167/12.13.7.Google Scholar
Wong, T. T.-Y., Ho, C. S.-H., and Tang, J.. 2017. ‘Defective Number Sense or Impaired Access? Differential Impairments in Different Subgroups of Children With Mathematics Difficulties’. Journal of Learning Disabilities 50 (1): 49–61.Google Scholar
Wu, C.-Y., Ho, M.-H. R., and Chen, S.-H. A.. 2012. ‘A Meta-Analysis of fMRI Studies on Chinese Orthographic, Phonological, and Semantic Processing’. NeuroImage. https://doi.org/10.1016/j.neuroimage.2012.06.047.Google Scholar
Wu, S. S., Willcutt, E. G., Escovar, E., and Menon, V.. 2014. ‘Mathematics Achievement and Anxiety and Their Relation to Internalizing and Externalizing Behaviors’. Journal of Learning Disabilities 47 (6): 503–14.Google Scholar
Wydell, T. N. 2019. ‘Developmental Dyslexia in Japanese’. In Verhoeven, L., Perfetti, C., & Pugh, K. (Eds.), Developmental Dyslexia across Languages and Writing Systems, 176–99. Cambridge University Press.Google Scholar
Wydell, T. N., and Kondo, T.. 2003. ‘Phonological Deficit and the Reliance on Orthographic Approximation for Reading: A Follow-up Study on an English-Japanese Bilingual with Monolingual Dyslexia’. Journal of Research in Reading 26 (1): 33–48. https://doi.org/10.1111/1467-9817.261004.Google Scholar
Wydell, T. N., and Butterworth, B.. 1999. ‘A Case Study of an English-Japanese Bilingual with Monolingual Dyslexia’. Cognition 70 (3): 273–305.Google Scholar
Wynd, D. 2015. ‘It Shouldn’t Be This Hard’: Children, Poverty and Disability. Child Poverty Action Group.Google Scholar
Wynn, K. 1990. ‘Children’s Understanding of Counting’. Cognition 36 (2): 155–93.Google Scholar
Wynn, K. 1992b. ‘Children’s Acquisition of the Number Words and the Counting System’. Cognitive Psychology 24 (2): 220–51.Google Scholar
Wyschkon, A., Kohn, J., Ballaschk, K., and Esser, G.. 2009. ‘Sind Rechenstörungen Genau so Häufig Wie Lese-Rechtschreibstörungen?’ Zeitschrift Fur Kinder- Und Jugendpsychiatrie Und Psychotherapie 37 (6): 499–512.Google Scholar
Wyse, D., and Goswami, U.. 2008. ‘Synthetic Phonics and the Teaching of Reading’. British Educational Research Journal 34 (6): 691–710.Google Scholar
Xu, M., Baldauf, D., Chang, C. Q., Desimone, R., and Tan, L. H.. 2017. ‘Distinct Distributed Patterns of Neural Activity Are Associated with Two Languages in the Bilingual Brain’. Science Advances 3 (7): e1603309.Google Scholar
Xu, M., Tan, L. H., and Perfetti, C.. 2019. ‘Developmental Dyslexia in Chinese’. In Verhoeven, L, Perfetti, C, and Pugh, K (eds.), Developmental Dyslexia across Languages and Writing Systems (pp. 200–226). Cambridge University Press. https://doi.org/10.1017/9781108553377.010.Google Scholar
Xu, M., Yang, J., Siok, W. T., and Tan, L. H.. 2015. ‘Atypical Lateralization of Phonological Working Memory in Developmental Dyslexia’. Journal of Neurolinguistics 33: 67–77. https://doi.org/10.1016/j.jneuroling.2014.07.004.Google Scholar
Yang, Y., Yang, Y. H., Li, J., Xu, M., and Bi., H.-Y. 2020. ‘An Audiovisual Integration Deficit Underlies Reading Failure in Nontransparent Writing Systems: An fMRI Study of Chinese Children with Dyslexia’. Journal of Neurolinguistics 54: 100884. https://doi.org/10.1016/j.jneuroling.2019.100884.Google Scholar
Yoon, H. W., Cho, K.-D., and Park, H. W.. 2005. ‘Brain Activation of Reading Korean Words and Recognizing Pictures by Korean Native Speakers: A Functional Magnetic Resonance Imaging Study’. The International Journal of Neuroscience 115 (6): 757–68.Google Scholar
Young, T., and Lewis, W. D.. 2015. ‘Educational Policy Implementation Revisited’. Educational Policy. https://doi.org/10.1177/0895904815568936.Google Scholar
Zaphiris, P., and Ioannou, A.. 2016. Learning and Collaboration Technologies: Third International Conference, LCT 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17–22, 2016, Proceedings. Springer International Publishing.Google Scholar
Zell, E., Krizan, Z., and Teeter, S. R.. 2015. ‘Evaluating Gender Similarities and Differences Using Metasynthesis’. The American Psychologist 70 (1): 10–20.Google Scholar
Zhang, J., and Norman, D. A.. 1995. ‘A Representational Analysis of Numeration Systems’. Cognition 57 (3): 271–95.Google Scholar
Zhang, X., and Lin, D.. 2015. ‘Pathways to Arithmetic: The Role of Visual-Spatial and Language Skills in Written Arithmetic, Arithmetic Word Problems, and Nonsymbolic Arithmetic’. Contemporary Educational Psychology 41 (April): 188–97.Google Scholar
Zhang, Y., and Zhou, X.. 2016. ‘Building Knowledge Structures by Testing Helps Children With Mathematical Learning Difficulty’. Journal of Learning Disabilities 49 (2): 166–75.Google Scholar
Zhou, X., Chen, C., Zang, Y., et al. 2007. ‘Dissociated Brain Organization for Single-Digit Addition and Multiplication’. NeuroImage 35 (2): 871–80.Google Scholar
Zhou, X., Wei, W., Zhang, Y., Cui, J., and Chen, C.. 2015. ‘Visual Perception Can Account for the Close Relation between Numerosity Processing and Computational Fluency’. Frontiers in Psychology 6 (September): 1364.Google Scholar
Zhukova, M., and Grigorenko, E.. 2019. ‘Developmental Dyslexia in Russian’. In Verhoeven, L, Perfetti, C, and Pugh, K (eds.), Developmental Dyslexia across Languages and Writing Systems (pp. 133–51). Cambridge University Press. https://doi.org/10.1017/9781108553377.007.Google Scholar
Ziegler, J. C., Bertrand, D., Tóth, D., et al. 2010. ‘Orthographic Depth and Its Impact on Universal Predictors of Reading’. Psychological Science 21 (4): 551–9. https://doi.org/10.1177/0956797610363406.Google Scholar
Ziegler, J. C., and Goswami, U.. 2005. ‘Reading Acquisition, Developmental Dyslexia, and Skilled Reading Across Languages: A Psycholinguistic Grain Size Theory’. Psychological Bulletin 131 (1): 3–29. https://doi.org/10.1037/0033-2909.131.1.3.Google Scholar
Ziegler, J. C., Perry, C., Ma-Wyatt, A., Ladner, D., and Schulte-Körne, G.. 2003. ‘Developmental Dyslexia in Different Languages: Language-Specific or Universal?’ Journal of Experimental Child Psychology 86 (3): 169–93. https://doi.org/10.1016/s0022-0965(03)00139-5.Google Scholar
Ziemann, U., and Siebner, H. R.. 2015. ‘Inter-Subject and Inter-Session Variability of Plasticity Induction by Non-Invasive Brain Stimulation: Boon or Bane?’ Brain Stimulation 8 (3): P662–3. https://doi.org/10.1016/j.brs.2015.01.409.Google Scholar
Zippert, E. L., and Rittle-Johnson, B.. 2020. ‘The Home Math Environment: More than Numeracy’. Early Childhood Research Quarterly 50 (January): 4–15.Google Scholar
Zuber, J., Pixner, S., Moeller, K., and Nuerk, H.-C.. 2009. ‘On the Language Specificity of Basic Number Processing: Transcoding in a Language with Inversion and Its Relation to Working Memory Capacity’. Journal of Experimental Child Psychology 102 (1): 60–77.Google Scholar

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  • References
  • Edited by Michael A. Skeide
  • Book: The Cambridge Handbook of Dyslexia and Dyscalculia
  • Online publication: 28 July 2022
  • Chapter DOI: https://doi.org/10.1017/9781108973595.038
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  • References
  • Edited by Michael A. Skeide
  • Book: The Cambridge Handbook of Dyslexia and Dyscalculia
  • Online publication: 28 July 2022
  • Chapter DOI: https://doi.org/10.1017/9781108973595.038
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  • References
  • Edited by Michael A. Skeide
  • Book: The Cambridge Handbook of Dyslexia and Dyscalculia
  • Online publication: 28 July 2022
  • Chapter DOI: https://doi.org/10.1017/9781108973595.038
Available formats
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