Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-24T02:41:10.404Z Has data issue: false hasContentIssue false
  • English
  • Français

Neuropsychology of Learning Disabilities: The Past and the Future

Published online by Cambridge University Press:  04 December 2017

Jack M. Fletcher  and
Elena L. Grigorenko
Jack M. Fletcher*
Affiliation:
University of Houston, Houston, Texas
Elena L. Grigorenko
Affiliation:
St. Petersburg University, St. Petersburg, Russia
*
Correspondence and reprint requests to: Jack M. Fletcher, Department of Psychology, University of Houston, 3695 Cullen Blvd., Heyne 126, Houston TX, 77204-5052. E-mail [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Over the past 50 years, research on children and adults with learning disabilities has seen significant advances. Neuropsychological research historically focused on the administration of tests sensitive to brain dysfunction to identify putative neural mechanisms underlying learning disabilities that would serve as the basis for treatment. Led by research on classifying and identifying learning disabilities, four pivotal changes in research paradigms have produced a contemporary scientific, interdisciplinary, and international understanding of these disabilities. These changes are (1) the emergence of cognitive science, (2) the development of quantitative and molecular genetics, (3) the advent of noninvasive structural and functional neuroimaging, and (4) experimental trials of interventions focused on improving academic skills and addressing comorbid conditions. Implications for practice indicate a need to move neuropsychological assessment away from a primary focus on systematic, comprehensive assessment of cognitive skills toward more targeted performance-based assessments of academic achievement, comorbid conditions, and intervention response that lead directly to evidence-based treatment plans. Future research will continue to cross disciplinary boundaries to address questions regarding the interaction of neurobiological and contextual variables, the importance of individual differences in treatment response, and an expanded research base on (a) the most severe cases, (b) older people with LDs, and (c) domains of math problem solving, reading comprehension, and written expression. (JINS, 2017, 23, 930–940)

Keywords

Learning disabilitiesNeuroimagingGeneticsInterventionResponse to interventionNeuropsychological assessment
Type
Section 4 – Pediatric Disorders
Information
Journal of the International Neuropsychological Society , Volume 23 , Special Issue 9-10: Special Issue: Commemoration of the 50th Anniversary of the International Neuropsychological Society , October 2017 , pp. 930 - 940
Copyright
Copyright © The International Neuropsychological Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ansari, D., & Lyons, D.M. (2016). Cognitive neuroscience and mathematics learning: How far have we come? Where do we need to go? ZDM Mathematics Education, 48, 379–383.Google Scholar
Bailey, S., Hoeft, F., Aboud, K., & Cutting, L. (2016). Anomalous gray matter patterns in specific reading comprehension deficit are independent of dyslexia. Annals of Dyslexia, 66, 256–274.CrossRefGoogle ScholarPubMed
Bates, T.C., Castles, A., Coltheart, M., Gillespie, N., Wright, M., & Martin, N.G. (2004). Behaviour genetic analyses of reading and spelling: A component processes approach. Australian Journal of Psychology, 56, 115–126.CrossRefGoogle Scholar
Belmont, L., Birch, H.G., & Belmont, I. (1968). Auditory-visual intersensory processing and verbal mediation. The Journal of Nervous and Mental Disease, 147(6), 562–569.Google Scholar
Benton, A.L. (1975). Development dyslexia: Neurological aspects. In W.J. Friedlander (Ed.), Advances in neurology, (Vol. 7, pp. 1–47). New York: Raven Press.Google Scholar
Benton, A.L., & Pearl, D. (Eds.) (1978). Dyslexia. New York: Oxford University Press.Google Scholar
Berninger, V.W. (2004). Understanding the graphia in developmental dysgraphia: A developmental neuropsychological perspective for disorders in producing written language. In D. Dewey & D. Tupper (Eds.), Developmental motor disorders: A neuropsychological perspective (pp. 189–233). New York: Guilford Press.Google Scholar
Burns, M.K., Petersen-Brown, S., Haegele, K., Rodriguez, M., Schmitt, M., Cooper, M., & VanDerHeyden, A.M. (2016). Meta-analysis of academic interventions derived from neuropsychological data. School Psychology Quarterly, 31, 28–42.CrossRefGoogle ScholarPubMed
Cain, K., & Barnes, M.A. (2017). Reading comprehension. In R.K. Parrila, K. Cain & D.L. Compton (Eds.), Theories of reading development (pp. 257–282). Amsterdam: John Benjamins.Google Scholar
Castro-Caldas, A., Petersson, K.M., Reis, A., Stone-Elander, S., & Ingvar, M. (1998). The illiterate brain: Learning to read and write during childhood influences the functional organization of the adult brain. Brain, 121, 1053–1063.CrossRefGoogle ScholarPubMed
Catts, H.W., Compton, D., Tomblin, B., & Bridges, M.S. (2012). Prevalence and nature of late-emerging poor readers. Journal of Educational Psychology, 10(4), 166–181.Google Scholar
Chen, Q., & Li, J. (2014). Association between individual differences in non-symbolic number acuity and math performance: A meta-analysis. Acta Psychologica, 148, 163–172.CrossRefGoogle ScholarPubMed
Chirkina, G.V., & Grigorenko, E.L. (2014). Tracking citations: A science detective story. Journal of Learning Disabilities, 7, 366–373.Google Scholar
Clark, K.A., Helland, T., Specht, K., Narr, K.L., Manis, F.R., Toga, A.W., & Hugdahl, K. (2014). Neuroanatomical precursors of dyslexia identified from pre-reading through to age 11. Brain, 137, 3136–3141.Google Scholar
Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204–256.Google Scholar
Connor, C.M., Morrison, F.J., Fishman, B.J., Schatschneider, C., & Underwood, P. (2007). The early years: Algorithm-guided individualized reading instruction. Science, 315, 464–465.Google Scholar
Cutting, L.E., Clements-Stephens, A., Pugh, K.R., Burns, S., Cao, A., Pekar, J.J., & Rimrodt, S.L. (2013). Not all reading disabilities are dyslexia: Distinct neurobiology of specific comprehension deficits. Brain Connectivity, 3(2), 199–211.CrossRefGoogle ScholarPubMed
DeFries, J.C., & Fulker, D.W. (1985). Multiple regression analysis of twin data. Behavior Genetics, 15(5), 467–473.Google Scholar
Dehaene, S. (2009). Reading in the brain: The new science of how we read. London: Penguin.Google Scholar
Dehaene, S., Cohen, L., Morais, J., & Kolinsky, R. (2015). Illiterate to literate: Behavioural and cerebral changes induced by reading acquisition. Nature Reviews Neuroscience, 16, 234–244.Google Scholar
Denckla, M.B., & Rudel, R.G. (1974). Rapid “Automatized” Naming of pictured objects, colors, letters, and numbers by normal children. Cortex, 10, 186–202.Google Scholar
Dennis, M., Landry, S.H., Barnes, M., & Fletcher, J.M. (2006). A model of neurocognitive function in spina bifida over the life span. Journal of the International Neuropsychological Society, 12(02), 285–296.Google Scholar
Doehring, D.G. (1978). The tangled web of behavioral research on developmental dyslexia. In A.L. Benton & D. Pearl (Eds.), Dyslexia (pp. 123–137). New York: Oxford University Press.Google Scholar
Dudbridge, F. (2013). Power and predictive accuracy of polygenic risk scores. PLoS Genetics, 9, e1003348.Google Scholar
Eicher, J.D., Powers, N.R., Miller, L.L., Mueller, K.L., Mascheretti, S., Marino, C., & Gruen, J.R. (2014). Characterization of the DYX2 locus on chromosome 6p22 with reading disability, language impairment, and IQ. Human Genetics, 133(7), 869–881.Google Scholar
Elliott, J., & Grigorenko, E.L. (2014). The dyslexia debate. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Ellis, A.W. (1984). The cognitive neuropsychology of developmental (and acquired) dyslexia: A critical survey. Cognitive Neuropsychology, 2, 169–205.Google Scholar
Ferstl, E.C., Neumann, J., Bogler, C., & von Cramon, D.Y. (2008). The extended language network: A meta-analysis of neuroimaging studies on text comprehension. Human Brain Mapping, 29, 581–593.Google Scholar
Fletcher, J.M., Lyon, G.R., Fuchs, L.S., & Barnes, M.A. (in press). Learning disabilities: From identification to intervention (2nd ed.). New York: Guilford Press.Google Scholar
Fletcher, J.M., & Miciak, J. (2017). Comprehensive cognitive assessments are not necessary for the identification and treatment of learning disabilities. Archives of Clinical Neuropsychology, 32, 2–7.Google Scholar
Fletcher, J.M., & Taylor, H.G. (1984). Neuropsychological approaches to children: Towards a developmental neuropsychology. Journal of Clinical and Experimental Neuropsychology, 6, 39–56.CrossRefGoogle ScholarPubMed
Fletcher, J.M., & Vaughn, S. (2009). Response to intervention: Preventing and remediating academic deficits. Child Development Perspectives, 3, 30–37.Google Scholar
Friend, A., DeFries, J.C., & Olson, R.K. (2008). Parental education moderates genetic influences on reading disability. Psychological Science, 19, 1124–1130.Google Scholar
Fuchs, D., Fuchs, L.S., & Vaughn, S. (2014). What is intensive instruction and why is it important? Teaching Exceptional Children, 46, 13–18.Google Scholar
Fuchs, L.S., & Fuchs, D. (1998). Treatment validity: A simplifying concept for reconceptualizing the identification of learning disabilities. Learning Disabilities Research and Practice, 4, 204–219.Google Scholar
Fuchs, L.S., Fuchs, D., Hamlett, C.L., Lambert, W., Stuebing, K., & Fletcher, J.M. (2008). Problem-solving and computational skill: Are they shared or distinct aspects of mathematical cognition? Journal of Educational Psychology, 100, 30–47.Google Scholar
Fuchs, L.S., Powell, S.R., Seethaler, P.M., Cirino, P.T., Fletcher, J.M., Fuchs, D., Hamlett, C.L., & Zumeta, R.O. (2009). Remediating number combination and word problem deficits among students with mathematical difficulties: A randomized control trial. Journal of Educational Psychology, 101, 561–576.Google Scholar
Galaburda, A.M., Sherman, G.P., Rosen, G.D., Aboitiz, F., & Geschwind, N. (1985). Developmental dyslexia: Four consecutive patients with cortical anomalies. Annals of Neurology, 18, 222–233.Google Scholar
García, J.R., & Cain, K. (2014). Decoding and reading comprehension: A meta-analysis to identify which reader and assessment characteristics influence the strength of the relationship in English. Review of Educational Research, 84(1), 74–111.CrossRefGoogle Scholar
Geary, D.C. (2005). Role of cognitive theory in the study of learning disability in mathematics. Journal of Learning Disabilities, 38, 305–307.Google Scholar
Geary, D.C. (2013). Early foundations for mathematics learning and their relations to learning disabilities. Current Directions in Psychological Science, 22(1), 23–27.Google Scholar
Geschwind, N., & Fusillo, M. (1966). Color-naming defects in association with Alexia. Archives of Neurology, 15, 137–146.Google Scholar
Graham, S., McKeown, D., Kiuhara, S., & Harris, K.R. (2012). A meta-analysis of writing instruction for students in the elementary grades. Journal of Educational Psychology, 104, 879–896.CrossRefGoogle Scholar
Greven, C.U., Kovas, Y., Willcutt, E.G., Petrill, S.A., & Plomin, R. (2014). Evidence for shared genetic risk between ADHD symptoms and reduced mathematics ability: A twin study. Journal of Child Psychology and Psychiatry, 55, 39–48.Google Scholar
Grigorenko, E. (in press). Genetics of (a)typical reading: An evolution of ideas. In G. Eden (Ed.), Handbook of the cognitive neuroscience of dyslexia. New York: John Wiley.Google Scholar
Grigorenko, E.L. (2005). A conservative meta-analysis of linkage and linkage-association studies of developmental dyslexia. Scientific Studies of Reading, 9, 285–316.Google Scholar
Harlaar, N., Kovas, Y., Dale, P.S., Petrill, S.A., & Plomin, R. (2012). Mathematics is differentially related to reading comprehension and word decoding: Evidence from a genetically sensitive design. Journal of Educational Psychology, 104, 622–634.Google Scholar
Hart, S., Petrill, S.A., Thompson, L., & Plomin, R. (2009). The abcs of math: A genetic analysis of mathematics and its links with reading ability and general cognitive ability. Journal of Educational Psychology, 101, 388–402.Google Scholar
Hart, S.A., Soden, B., Johnson, W., Schatschneider, C., & Taylor, J. (2013). Expanding the environment: Gene × school-level SES interaction on reading comprehension. Journal of Child Psychology and Psychiatry, 54, 1047–1055.CrossRefGoogle ScholarPubMed
Hawke, J.L., Wadsworth, S.J., Olson, R.K., & DeFries, J.C. (2007). Etiology of reading difficulties as a function of gender and severity. Reading and Writing, 20, 13–25.Google Scholar
Hinshelwood, J. (1895). Word-blindness and visual memory. Lancet, ii, 1564–1570.CrossRefGoogle Scholar
Iuculano, T., Rosenberg-Lee, M., Richardson, J., Tenison, C., Fuchs, L., Supekar, K., & Menon, V. (2015). Cognitive tutoring induces widespread neuroplasticity and remediates brain function in children with mathematical learning disabilities. Nature Communications, 6, 8453. doi: 10.1038/ncomms9453 Google Scholar
Keenan, J.M., Betjemann, R.S., Wadsworth, S.J., DeFries, J.C., & Olson, R.K. (2006). Genetic and environmental influences on reading and listening comprehension. Journal of Research on Reading, 29, 75–91.Google Scholar
Keenan, J.M., Betjemann, R.S., & Olson, R.K. (2008). Reading comprehension tests vary in the skills they assess: Differential dependence on decoding and oral comprehension. Scientific Studies of Reading, 12, 281–300.Google Scholar
Kinsbourne, M., & Warrington, E.K. (1963). Developmental factors in reading and writing backwardness. British Journal of Psychology, 54, 145–156.Google Scholar
Kirk, S.A. (1963). Behavioral diagnosis and remediation of learning disabilities. Conference on Exploring Problems of the Perceptually Handicapped Child, 1, 1–23.Google Scholar
Leach, J.M., Scarborough, H.S., & Rescorla, L. (2003). Late-emerging reading disabilities. Journal of Educational Psychology, 95, 211–224.Google Scholar
Liberman, A.M., Cooper, F.S., Shankweiler, D., & Studdert-Kennedy, M. (1967). Perception of the speech code. Psychological Review, 74, 431–461.Google Scholar
Liberman, I.Y. (1971). Basic research in speech and lateralization of language. Bulletin of the Orton Society, 21, 72–87.Google Scholar
Lovett, M.W., Frijters, J.C., Wolf, M.A., Steinbach, K.A., Sevcik, R.A., & Morris, R.D. (in press). Early intervention for children at risk for reading disabilities: The impact of grade at intervention and individual differences on intervention outcomes. Journal of Educational Psychology.Google Scholar
Lovett, M.W., Lacerenza, L., Borden, S.L., Frijters, J.C., Steinbach, K.A., & DePalma, M. (2000). Components of effective remediation for developmental reading disabilities: Combining phonological and strategy-based instruction to improve outcomes. Journal of Educational Psychology, 92, 263–283.Google Scholar
Macmann, G.M., Barnett, D.W., Lombard, T.J., Belton-Kocher, E., & Sharpe, M.N. (1989). On the actuarial classification of children: Fundamental studies of classification agreement. The Journal of Special Education, 23, 127–149.Google Scholar
Mahone, M., & Denckla, M.B. (in press). Attention-Deficit/Hyperactivity Disorder. Journal of the International Neuropsychological Association.Google Scholar
Mapou, R. (2009). Adult learning disabilities and ADHD: Research informed assessment. New York: Oxford Press.Google Scholar
Marino, C., Citterio, A., Giorda, R., Facoetti, A., Menozzi, G., Vanzin, L., & Molteni, M. (2007). Association of short-term memory with a variant within DYX1C1 in developmental dyslexia. Genes, Brain, & Behavior, 6, 640–646.Google Scholar
Mascheretti, S., Riva, V., Giorda, R., Beri, S., Lanzoni, L.F.E., Cellino, M.R., & Marino, C. (2014). KIAA0319 and ROBO1: Evidence on association with reading and pleiotropic effects on language and mathematics abilities in developmental dyslexia. Journal of Human Genetics, 59, 189–197.Google Scholar
Matejko, A.A., & Ansari, D. (2015). Drawing connections between white matter and numerical and mathematical cognition: A literature review. Neuroscience & Biobehavioral Reviews, 48, 35–52.Google Scholar
Mathes, P.G., Denton, C.A., Fletcher, J.M., Anthony, J.L., Francis, D.J., & Schatschneider, C. (2005). An evaluation of two reading interventions derived from diverse models. Reading Research Quarterly, 40, 148–183.Google Scholar
McGrath, L.M., Pennington, B.F., Shanahan, M.A., Santerre‐Lemmon, L.E., Barnard, H.D., Willcutt, E. G., & Olson, R.K. (2011). A multiple deficit model of reading disability and attention‐deficit/hyperactivity disorder: Searching for shared cognitive deficits. Journal of Child Psychology and Psychiatry, 52(5), 547–557.Google Scholar
Melby-Lervåg, M., Lyster, S.A.H., & Hulme, C. (2012). Phonological skills and their role in learning to read: A meta-analytic review. Psychological Bulletin, 138, 322–148.Google Scholar
Melby-Lervåg, M., Redick, T., & 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, 11, 512–534.CrossRefGoogle ScholarPubMed
Morris, R.D., Lovett, M.W., Wolf, M.A., Sevcik, R.A., Steinbach, K.A., Frijters, J.C., & Shapiro, M. (2012). Multiple-component remediation for developmental reading disabilities: IQ, socioeconomic status, and race as factors in remedial outcome. Journal of Learning Disabilities, 45, 99–127.CrossRefGoogle Scholar
Morris, R., & Fletcher, J.M. (1988). Classification in neuropsychology: A theoretical framework and research paradigm. Journal of Clinical and Experimental Neuropsychology, 10, 640–658.Google Scholar
Naples, A.J., Chang, J.T., Katz, L., & Grigorenko, E.L. (2009). Insights into the etiologiy of phonological awareness and rapid naming. Biological Psychiatry, 80, 226–239.CrossRefGoogle Scholar
Olson, R.K., Hulslander, J., Christopher, M., Keenan, J.M., Wadsworth, S.J., Willcutt, E.G., & DeFries, J.C. (2013). Genetic and environmental influences on writing and their relations to language and reading. Annals of Dyslexia, 63, 25–43.Google Scholar
Olson, R.K., Keenan, J.M., Byrne, B., & Samuelsson, S. (2014). Why do children differ in their development of reading and related skills? Scientific Studies of Reading, 18, 38–54.Google Scholar
Orton, S. (1928). Specific reading disability—strephosymbolia. Journal of the American Medical Association, 90, 1095–1099.Google Scholar
Paulesu, E., Démonet, J.F., Fazio, F., McCrory, E., Chanoine, V., Brunswick, N., & Frith, U. (2001). Dyslexia: Cultural diversity and biological unity. Science, 291, 2165–2167.Google Scholar
Pennington, B.F. (2006). From single to multiple deficit models of developmental disorders. Cognition, 101, 385–413.Google Scholar
Pennington, B.F. (2009). Diagnosing learning disorders: A neuropsychological framework (2nd ed.), New York: Guilford.Google Scholar
Pennington, B.F., & Peterson, R. (2015). Neurodevelopmental disorders: Learning disorders. In A. Tasman, J. Kay, J.A. Lieberman, M.B. First & M.R. Riba (Eds.), Psychiatry (4th ed.), Chichester, UK: John Wiley & Sons.Google Scholar
Planton, S., Jucla, M., Roux, F.E., & Démonet, J.F. (2013). The “handwriting brain”: A meta-analysis of neuroimaging studies of motor versus orthographic processes. Cortex, 49, 2772–2787.Google Scholar
Plomin, R., & Kovas, Y. (2005). Generalist genes and learning disabilities. Psychological Bulletin, 131, 592–617.Google Scholar
Rae, C., Lee, M.A., Dixon, R.M., Blamire, A.M., Thompson, C.H., Styles, P., & Stein, J.F. (1998). Metabolic abnormalities in developmental dyslexia detected by 1 H magnetic resonance spectroscopy. The Lancet, 351(9119), 1849–1852.Google Scholar
Raschle, N.M., Becker, B.L.C., Smith, S., Fehlbaum, L.V., Wang, Y., & Gaab, N. (2017). Investigating the influences of language delay and/or familial risk for dyslexia on brain structure in 5-year-olds. Cerebral Cortex, 27, 764–776.Google Scholar
Richards, T., Berninger, V., & Fayol, M. (2009). fMRI activation differences between 11-year-old good and poor spellers’ access in working memory to temporary and long-term orthographic representations. Journal of Neurolinguistics, 22, 327–353.Google Scholar
Rivera, S.M., Reiss, A.L., Eckert, M.A., & Menon, V. (2005). Developmental changes in mental arithmetic: Evidence for increased functional specialization in the left inferior parietal cortex. Cerebral Cortex, 15, 1779–1790.Google Scholar
Rourke, B.P. (1975). Brain–behavior relationships in children with learning disabilities: A research program. American Psychologist, 30, 911–920.Google Scholar
Rourke, B.P. (1978). Neuropsychological research in reading retardation. In A.L. Benton & D. Pearl (Eds.), Dyslexia (pp. 139–172). New York: Oxford University Press.Google Scholar
Rourke, B.P. (Ed.) (1985). Neuropsychology of learning disabilities: Essentials of subtype analysis. New York: Guilford Press.Google Scholar
Rourke, B.P. (1989). Nonverbal learning disabilities: The syndrome and the model. New York: Guilford Press.Google Scholar
Rourke, B.P., & Finlayson, M.A.J. (1978). Neuropsychological significance of variations in patterns of academic performance: Verbal and visual–spatial abilities. Journal of Pediatric Psychology, 3, 62–66.Google Scholar
Rumsey, J.M., Zametkin, A.J., Andreason, P., Hanchan, A.P., Hamburger, S.D., Aquino, T., & Cohen, R.M. (1994). Normal activation of frontotemporal language cortex in dyslexia, as measured with oxygen 15 positron emission tomography. Archives of Neurology, 51, 27–38.Google Scholar
Rutter, M., & Yule, W. (1975). The concept of specific reading retardation. Journal of Child Psychology and Psychiatry, 16, 181–197.Google Scholar
Satz, P., & Sparrow, S. (1970). Specific developmental dyslexia: A theoretical formulation. In D.F. Bakker & P. Satz (Eds.), Specific reading disability: Advances in theory and method (pp. 17–39). Rotterdam: Rotterdam University Press.Google Scholar
Scammacca, N.K., Roberts, G.J., Cho, E., Williams, K.J., Roberts, G., Vaughn, S.R., & Carroll, M. (2016). A century of progress reading interventions for students in grades 4–12, 1914–2014. Review of Educational Research, 86, 756–800.Google Scholar
Scerri, T.S., & Schulte-Körne, G. (2010). Genetics of developmental dyslexia. European Child & Adolescent Psychiatry, 19, 179–197.Google Scholar
Schneider, W.J., & Kaufman, A. (2017). Let’s not do away with comprehensive cognitive assessments just yet. Archives of Clinical Neuropsychology, 32, 8–20.Google Scholar
Schulte-Körne, G. (2001). Genetics of reading and spelling disorder. Journal of Child Psychology and Psychiatry, 42, 985–997.Google Scholar
Schultz, R.T., Cho, N.K., Staib, L.H., Kier, L.E., Fletcher, J.M., Shaywitz, S.E., & Duncan, J.S. (1994). Brain morphology in normal and dyslexic children: The influence of sex and age. Annals of Neurology, 35, 732–742.Google Scholar
Seidenberg, M. (2017). Language at the speed of sight: How we read, why so many can’t, and what can be done about it. New York: Basic Books.Google Scholar
Shaywitz, S.E., Shaywitz, B.A., Pugh, K.R., Fulbright, R.K., Constable, R.T., Mencl, W.E., & Gore, J.C. (1998). Functional disruption in the organization of the brain for reading in dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 95, 2636–2641.Google Scholar
Shavelson, R., & Towne, L. (2002). Science and education. Washington, DC: National Academy of Sciences.Google Scholar
Snowling, M., & Hulme, C. (1994). The development of phonological skills. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 346(1315), 21–27.Google Scholar
Snowling, M., & Melby-Lervåg, M. (2016). Oral language deficits in familial dyslexia: A meta-analysis and review. Psychological Bulletin, 142, 498–545.Google Scholar
Stothard, S.E., & Hulme, C. (1992). Reading comprehension difficulties in children: The role of language comprehension and working memory skills. Reading and Writing, 4, 245–256.Google Scholar
Stuebing, K.K., Barth, A.E., Trahan, L., Reddy, R., Miciak, J., & Fletcher, J.M. (2015). Are child characteristics strong predictors of response to intervention? A meta-analysis. Review of Educational Research, 85, 395–429.Google Scholar
Stuebing, K.K., Fletcher, J.M., LeDoux, J.M., Lyon, G.R., Shaywitz, S.E., & Shaywitz, B.A. (2002). Validity of IQ-discrepancy classifications of reading disabilities: A meta-analysis. American Educational Research Journal, 39, 469–518.CrossRefGoogle Scholar
Swanson, H.L., Harris, K., & Graham, S. (Eds.) (2013). Handbook of learning disabilities (2nd ed.), New York: Guilford Press.Google Scholar
Taylor, J., Roehrig, A.D., Soden Hensler, B., Connor, C.M., & Schatschneider, C. (2010). Teacher quality moderates the genetic effects on early reading. Science, 328, 512–514.Google Scholar
Taylor, J.S.H., Rastle, K., & Davis, M.H. (2013). Can cognitive models explain brain activation during word and pseudoword reading? A meta-analysis of 36 neuroimaging studies. Psychological Bulletin, 139, 766–791.Google Scholar
Torgesen, J.K., Alexander, A.W., Wagner, R.K., Rashotte, C.A., Voeller, K.K.S., & Conway, T. (2001). Intensive remedial instruction for children with severe reading disabilities: Immediate and long-term outcomes from two instructional approaches. Journal of Learning Disabilities, 34, 33–58.Google Scholar
Tosto, M.G., Petrill, S.A., Halberda, J., Trzaskowski, M., Tikhomirova, T.N., Bogdanova, O.Y., & Plomin, R. (2014). Why do we differ in number sense? Evidence from a genetically sensitive investigation. Intelligence, 43, 35–46.Google Scholar
Vellutino, F.R., Scanlon, D.M., Sipay, E.R., Small, S.G., Pratt, A., Chen, R., & Denckla, M.B. (1996). Cognitive profiles of difficult-to-remediate and readily remediated poor readers: Early intervention as a vehicle for distinguishing between cognitive and experiential deficits as basic causes of specific reading disability. Journal of Educational Psychology, 88, 601–638.Google Scholar
Vellutino, F.R. (1978). Toward an understanding of dyslexia: Psychological factors in specific reading disability. In A.L. Benton & D. Pearl (Eds.), Dyslexia (pp. 61–112). New York: Oxford University Press.Google Scholar
Vogel, A.C., Petersen, S.E., & Schlaggar, B.L. (2014). The VWFA: It’s not just for words anymore. Frontiers in Human Neuroscience, 8, 1–10.Google Scholar
Wadsworth, S., Olson, R., & DeFries, J. (2010). Differential genetic etiology of reading difficulties as a function of IQ: An update. Behavior Genetics, 40, 751–758.Google Scholar
Waber, D. (2010). Rethinking learning disabilities: Understanding children who struggle in school. New York: Guilford.Google Scholar
Willcutt, E.G., Betjemann, R.S., McGrath, L.M., Chhabildas, N.A., Olson, R.K., DeFries, J.C., & Pennington, B.F. (2010). Etiology and neuropsychology of comorbidity between RD and ADHD: The case for multiple-deficit models. Cortex, 46, 1345–1361.Google Scholar
Willcutt, E.G., Petrill, S.A., Wu, S., Boada, R., DeFries, J.C., Olson, R.K., & Pennington, B.F (2013). Comorbidity between reading disability and math disability: Concurrent psychopathology, functional impairment, and neuropsychological functioning. Journal of Learning Disabilities, 46, 500–516.Google Scholar
Wimmer, H., & Mayringer, H. (2002). Dysfluent reading in the absence of spelling difficulties: A specific disability in regular orthographies. Journal of Educational Psychology, 94, 272–277.Google Scholar
Wolf, M., & Bowers, P.G. (1999). The double-deficit hypothesis for the developmental dyslexias. Journal of Educational Psychology, 91, 415–438.Google Scholar
Ziegler, J.C., & Goswami, U. (2005). Reading acquisition, developmental dyslexia, and skilled reading across languages: A psycholinguistic grain size theory. Psychological Bulletin, 131, 3–29.Google Scholar