Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-27T18:18:28.275Z Has data issue: false hasContentIssue false

Complete List of References

Published online by Cambridge University Press:  15 September 2018

Adriana Galván
Affiliation:
University of California, Los Angeles
Get access
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 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

Complete List of References

Abe, J., and Izard, C. (1999). The development functions of emotions: an analysis in terms of differential emotions theory. Cognition and Emotion, 13, 523549.CrossRefGoogle Scholar
Adolescent Sleep Working Group, Committee on Adolescence, and Council on School Health (2014). School start times for adolescents. Pediatrics, 134, 642649.CrossRefGoogle Scholar
Adolphs, R. (2002). Recognizing emotion from facial expressions: psychological and neurological mechanisms. Behavioral and Cognitive Neuroscience Reviews, 1, 2162.CrossRefGoogle ScholarPubMed
Adrien, J., Faure, M., Perrot, A., Hameury, L., Garreau, B., Barthelemy, C., and Sauvage, D. (1991). Autism and family home movies: preliminary findings. Journal of Autism Developmental Disorder, 21, 4349.Google Scholar
Ahmed, M., Ong, K., Morrell, D., Cox, L., Drayer, N., Perry, L., and Dunger, D. (1999). Longitudinal study of leptin concentrations during puberty: sex differences and relationship to changes in body composition. Journal of Clinical Endocrinology and Metabolism, 84(3), 899905.Google ScholarPubMed
Ainsworth, M. (1989). Attachments beyond infancy. American Psychologist, 44(4), 709716.Google Scholar
Albert, D., Chein, J., and Steinberg, L. (2013). The teenage brain: peer influences on adolescent decision making. Current Directions in Psychological Science, 22, 114119.CrossRefGoogle ScholarPubMed
Alfano, C.A., Reynolds, K., Scott, N., Dahl, R.E., and Mellman, T.A. (2013). Polysomnographic sleep patterns of non-depressed, non-medicated children with generalized anxiety disorder. Journal of Affective Disorders, 147, 379384.Google Scholar
Allen, J.P., Porter, M.R., McFarland, F.C., Marsh, P., and McElhaney, K.B. (2005). The two faces of adolescents' success with peers: adolescent popularity, social adaptation and deviant behavior. Child Development, 76, 747760.Google Scholar
Allison, T., Ginter, H., McCarthy, G., Nobre, A., Puce, A., Luby, M., and Spencer, D. (1994). Face recognition in human extrastriate cortex. Journal of Neurophysiology, 71, 821825.Google Scholar
Allison, T., Puce, A., and McCarthy, G. (2000). Social perception from visual cues: role of the STS region. Trends in Cognitive Science, 4, 267278.CrossRefGoogle ScholarPubMed
American Academy of Pediatrics, Committee on Adolescence (1996). The adolescent's right to confidential care when considering abortion. Pediatrics, 97, 746751.CrossRefGoogle Scholar
American Psychological Association (1989). Amicus curiae brief in Hodgson v. Minnesota, 497 U.S. 417 (1990).Google Scholar
Amodio, D., and Frith, C. (2006). Meeting of the minds: the medial frontal cortex and social cognition. Nature Reviews Neuroscience, 7, 268277.CrossRefGoogle ScholarPubMed
Andersen, S., Dumont, N., and Teicher, M. (1997). Developmental differences in dopamine synthesis inhibition by (+/−)-7-OH-DPAT. Naunyn-Schmiedebergs Archives of Pharmacology, 356, 173181.CrossRefGoogle ScholarPubMed
Andersen, S., and Gazzara, R. (1993). The ontogeny of apomorphine-induced alterations of neostriatal dopamine release: effects of spontaneous release. Journal of Neurochemistry, 61, 22472255.CrossRefGoogle ScholarPubMed
Andersen, S., Thompson, A., Rutstein, M., Hostetter, J., and Teicher, M. (2000). Dopamine receptor pruning in prefrontal cortex during the periadolescent period in rats. Synapse, 37, 167169.3.0.CO;2-B>CrossRefGoogle ScholarPubMed
Anderson, S., Dallal, G., and Must, A. (2003). Relative weight and race influence average age at menarche: results from two nationally representative surveys of US girls studied 25 years apart. Pediatrics, 111(4 Pt. 1), 844850.CrossRefGoogle ScholarPubMed
Arnett, J. (2011). Emerging adulthood(s): the cultural psychology of a new life stage. In Jensen, L. (ed.), Bridging cultural and developmental approaches to psychology: new synthesis in theory, research and policy (pp. 255275). Oxford: Oxford University Press.Google Scholar
Asarnow, L., McGlinchey, E., and Harvey, A. (2014). The effects of bedtime and sleep duration on academic and emotional outcomes in a nationally representative sample of adolescents. Journal of Adolescent Health, 54, 350356.CrossRefGoogle Scholar
Aylward, E., Park, J., Field, K., Parsons, A., Richards, T., Cramer, S., and Meltzoff, A. (2005). Brain activation during face perception: evidence of a developmental change. Journal of Cognitive Neuroscience, 17, 308319.CrossRefGoogle ScholarPubMed
Baenninger, M. (1994). The development of face recognition: featural or configurational processing? Journal of Experimental Child Psychology, 57, 377396.CrossRefGoogle ScholarPubMed
Baird, A., Gruber, S., Fein, D., Maas, L., Steingard, R., Renshaw, P., and Yurgelun-Todd, D. (1999). Functional magnetic resonance imaging of facial affect recognition in children and adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 195199.CrossRefGoogle ScholarPubMed
Banks, S., Eddy, K., Angstadt, M., Nathan, P., and Phan, K. (2007). Amygdala–frontal connectivity during emotion regulation. Social Cognitive and Affective Neuroscience, 2, 303312.Google Scholar
Barkley-Levenson, E., and Galván, A. (2014). Neural representation of expected value in the adolescent brain. Proceedings of the National Academy of Sciences USA, 111, 16461651.CrossRefGoogle ScholarPubMed
Barkley-Levenson, E., and Galván, A. (2016). Eye blink rate predicts reward decisions in adolescents. Developmental Science.Google Scholar
Barnes, C. (1979). Memory deficits associated with senescence: a neurophysiological and behavioral study in the rat. Journal of Comparative Physiology and Psychology, 93, 74104.Google Scholar
Baron-Cohen, S., Wheelwright, S., Cox, A., Baird, G., Charman, T., Swettenham, J., Drew, A., and Doehring, P. (2000). Early identification of autism by the Checklist for Autism in Toddlers (CHAT). Journal of the Royal Society of Medicine, 93, 521525.Google Scholar
Barrera, M., and Maurer, D. (1981). The perception of facial expressions by the three-month-old. Child Development, 52, 203206.CrossRefGoogle ScholarPubMed
Basch, C., Basch, C., Ruggles, K., and Rajan, S. (2014). Prevalence of sleep duration on an average school night among 4 nationally representative successive samples of American high school students, 2007–2013. Preventing Chronic Disease, 11, E216.CrossRefGoogle Scholar
Basser, P., Mattiello, J., and LeBihan, D. (1994). MR diffusion tensor spectroscopy and imaging. Biophysical Journal, 66, 259267.CrossRefGoogle ScholarPubMed
Basser, P., and Pierpaoli, C. (2011). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. 1996. Journal of Magnetic Resonance, 213, 560570.CrossRefGoogle ScholarPubMed
Baumeister, R., and Leary, M. (1995). The need to belong: desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117, 497529.CrossRefGoogle ScholarPubMed
Bavelier, D., and Neville, H. (2002). Cross-modal plasticity: where and how? Nature Reviews Neuroscience, 3, 443452.CrossRefGoogle ScholarPubMed
Beard, J. (2003). Iron deficiency alters brain development and functioning. Journal of Nutrition, 133(5 Suppl. 1), 1468S1472S.Google Scholar
Bell, M., and Sisk, C. (2013). Dopamine mediates testosterone-induced social reward in male Syrian hamsters. Endocrinology, 154, 12251234.CrossRefGoogle ScholarPubMed
Belsky, J., and Jaffee, S. (2006). The multiple determinants of parenting. In Cicchetti, D. and Cohen, D. (eds.), Developmental psychopathology (2nd edn., vol. 3, pp. 38–85). Hoboken, NJ: Wiley and Sons.Google Scholar
Belsky, J., Steinberg, L., and Draper, P. (1991). Childhood experience, interpersonal development, and reproductive strategy: an evolutionary theory of socialization. Child Development, 62, 647670.CrossRefGoogle ScholarPubMed
Benedict, R. (1934). Patterns of culture. New York: Houghton Mifflin.Google Scholar
Berquin, P., Giedd, J., Jacobsen, L., Hamburger, S., Krain, A., Rapoport, J., and Castellanos, F.X. (1998). Cerebellum in attention-deficit hyperactivity disorder: a morphometric MRI study. Neurology, 50, 10871093.CrossRefGoogle ScholarPubMed
Berry, H., O'Grady, D., Perlmutter, L., and Bofinger, M. (1979). Intellectual development and achievement in children treated early for phenylketonuria. Developmental Medicine and Child Neurology, 21, 311320.CrossRefGoogle ScholarPubMed
Bertenthal, B., and Campos, J. (1990). A systems approach to the organizing effects of self-produced locomotion during infancy. In Rovee-Collier, C. and Lipsitt, L. (eds.), Advances in infancy research (pp. 134156). Amsterdam: Elsevier.Google Scholar
Biswal, B., Yetkin, F., Haughton, V., and Hyde, J. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance Medicine, 34, 537541.CrossRefGoogle ScholarPubMed
Bjork, J., Knutson, B., Fong, G., Caggiano, D., Bennett, S., and Hommer, D. (2004). Incentive-elicited brain activation in adolescents: similarities and differences from young adults. Journal of Neuroscience, 24, 17931802.CrossRefGoogle ScholarPubMed
Bjork, J., Smith, A., Chen, G., and Hommer, D. (2010). Adolescents, adults and rewards: comparing motivational neurocircuitry recruitment using fMRI. PLoS One, 5, e11440.CrossRefGoogle ScholarPubMed
Bjork, J., Smith, A., Chen, G., and Hommer, D. (2011). Psychosocial problems and recruitment of incentive neurocircuitry: exploring individual differences in healthy adolescents. Developmental Cognitive Neuroscience, 1, 570577.CrossRefGoogle ScholarPubMed
Bjorklund, D., and Harnishfeger, K. (1990). The resources construct in cognitive development: diverse sources of evidence and a theory of inefficient inhibition. Developmental Review, 10, 4871.CrossRefGoogle Scholar
Blake, P., and McAuliffe, K. (2011). “I had so much it didn't seem fair”: eight-year-olds reject two forms of inequity. Cognition, 120, 215224.CrossRefGoogle ScholarPubMed
Blakemore, S. (2008). The social brain in adolescence. Nature Reviews Neuroscience, 9, 267277.Google Scholar
Blakemore, S., and Mills, K. (2014). Is adolescence a sensitive period for sociocultural processing? Annual Review of Psychology, 65, 187207.CrossRefGoogle ScholarPubMed
Blakemore, S.J., Burnett, S., and Dahl, R.E. (2010). The role of puberty in the developing adolescent brain. Human Brain Mapping, 31, 926933.Google Scholar
Blum, K., Braverman, E., Holder, J., Lubar, J.F., Monastra, V., Miller, D., Lubar, J.O., Chen, T.J., Comings, D. (2000). Reward deficiency syndrome: a biogenetic model for the diagnosis and treatment of impulsive, addictive and compulsive behaviors. Journal of Psychoactive Drugs, 2, 1112.CrossRefGoogle Scholar
Blumenthal, H., Leen-Feldner, E., Babson, K., Gahr, J., Trainor, C., and Frala, J. (2011). Elevated social anxiety among early maturing girls. Developmental Psychology, 47, 11331140.Google Scholar
Boddaert, N., Chabane, N., Gervais, H., Good, C., Bourgeois, M., Plumet, M.H, Barthelemy, C., Mouren, M.C., Artiges, E., Samson, Y., Brunelle, F., Frackowiak, R.S., and Zilbovicius, M. (2004). Superior temporal sulcus anatomical abnormalities in childhood autism: a voxel-based morphometry MRI study. Neuroimage, 23, 364369.CrossRefGoogle ScholarPubMed
Bola, L., Zimmerman, M., Mostowski, P., Jednorog, K., Marchewka, A., Rotkowski, P., and Szwed, M. (2017). Task-specific reorganization of the auditory cortex in deaf humans. Proceedings of the National Academy of Sciences USA, 114, E600E609.CrossRefGoogle ScholarPubMed
Bolanos, C., Glatt, S., and Jackson, D. (1998). Subsensitivity to dopaminergic drugs in periadolescent rats: a behavioral and neurochemical analysis. Developmental Brain Research, 111, 2533.CrossRefGoogle ScholarPubMed
Bonnie, R. (1993). The competence of criminal defendants: beyond Dusky and Drope. University of Miami Law Review, 47, 539601.Google Scholar
Bonnie, R., and Grisso, T. (2000). Adjudicative competence and youthful offenders. In Grisso, T. and Schwartz, R. (eds.), Youth on trial: a developmental perspective on juvenile justice (pp. 73103). Chicago, IL: University of Chicago Press.Google Scholar
Bonnie, R., and Scott, E. (2013). The teenage brain: adolescent brain research and the law. Current Directions in Psychological Science, 22, 158161.CrossRefGoogle Scholar
Bos, P., van Honk, J., Ramsey, N., Stein, D., and Hermans, E. (2013). Testosterone administration in women increases amygdala responses to fearful and happy faces. Psychoneuroendocrinology, 38, 808817.CrossRefGoogle ScholarPubMed
Botvinick, M., Cohen, J., and Carter, C. (2004). Conflict monitoring and anterior cingulate cortex: an update. Trends in Cognitive Neuroscience, 8, 539546.CrossRefGoogle ScholarPubMed
Boucher, J., and Lewis, V. (1992). Unfamiliar face recognition in relatively able autistic children. Journal of Child Psychology and Psychiatry, 33, 843859.Google Scholar
Braams, B., van Duijvenvoorde, A., Peper, J., and Crone, E. (2015). Longitudinal changes in adolescent risk-taking: a comprehensive study of neural responses to rewards, pubertal development, and risk-taking behavior. Journal of Neuroscience, 35, 72267238.Google Scholar
Bradford Cannon, W. (1929). Bodily changes in pain, hunger, fear, and rage. New York: Appleton-Century-Crofts.Google Scholar
Braitenberg, V. (2001). Brain size and number of neurons: an exercise in synthetic neuroanatomy. Journal of Computational Neuroscience, 10, 7177.CrossRefGoogle ScholarPubMed
Bramen, J.E., Hranilovich, J.A., Dahl, R.E., Chen, J., Rosso, C., Forbes, E.E., and Sowell, E.R. (2012). Sex matters during adolescence: testosterone-related cortical thickness maturation differs between boys and girls. PLoS One, 7, e33850.CrossRefGoogle ScholarPubMed
Breiter, H., Etcoff, N., Whalen, P., Kennedy, W., Rauch, S., Buckner, R., Strauss, M.M., Hyman, S.E., and Rosen, B. (1996). Response and habituation of the human amygdala during visual processing of facial expression. Neuron, 17, 875887.CrossRefGoogle ScholarPubMed
Brenhouse, H., and Andersen, S. (2008). Delayed extinction and stronger reinstatement of cocaine conditioned place preference in adolescent rats, compared to adults. Behavioral Neuroscience, 122, 460465.CrossRefGoogle ScholarPubMed
Brenhouse, H., Sonntag, K., and Andersen, S. (2008). Transient D1 dopamine receptor expression on prefrontal cortex projection neurons: relationship to enhanced motivational salience of drug cues in adolescence. Journal of Neuroscience, 28, 23752382.Google Scholar
Brooks-Gunn, J., Warren, M.P., Rosso, J., and Gargiulo, J. (1987). Validity of self-report measures of girls’ pubertal status. Child Development, 58, 829-841.CrossRefGoogle ScholarPubMed
Brown, T., Lugar, H., Coalson, R., Miezin, F., Petersen, S., and Schlaggar, B. (2005). Developmental changes in human cerebral functional organization for word generation. Cerebral Cortex, 15(3), 275290.CrossRefGoogle ScholarPubMed
Bruner, J. (1972). Nature and uses of immaturity. American Psychologist, 27, 687708.CrossRefGoogle Scholar
Brunner, R., Berch, D., and Berry, H. (1987). Phenylketonuria and complex spatial visualization: an analysis of information processing. Developmental Medicine and Child Neurology, 29, 460468.CrossRefGoogle ScholarPubMed
Buckhalt, J. (2011). Insufficient sleep and the socioeconomic status achievement gap. Child Development Perspectives, 5, 5965.Google Scholar
Bullock, M., and Russell, J. (1985). Further evidence on preschoolers’ interpretation of facial expressions. International Journal of Behavioral Development, 8, 1538.CrossRefGoogle Scholar
Bunge, S.A., Dudukovic, N.M., Thomason, M.E., Vaidya, C.J., and Gabrieli, J.D.E. (2002). Immature frontal lobe contributions to cognitive control in children: evidence from fMRI. Neuron, 33, 301311.CrossRefGoogle ScholarPubMed
Burklund, L., Eisenberger, N., and Lieberman, M. (2007). The face of rejection: rejection sensitivity moderates dorsal anterior cingulate activity to disapproving facial expressions. Social Neuroscience, 2, 238253.Google Scholar
Burnett, S., Bault, N., Coricelli, G., and Blakemore, S. (2010). Adolescents’ heightened risk-seeking in a probabilistic gambling task. Cognitive Development, 25, 183196.CrossRefGoogle Scholar
Burnett, S., Bird, G., Moll, J., Frith, C., and Blakemore, S.-J. (2009). Development during adolescence of the neural processing of social emotion. Journal of Cognitive Neuroscience, 21, 17361750.CrossRefGoogle ScholarPubMed
Burnett, S., Sebastian, C., Cohen Kadosh, K., and Blakemore, S.J. (2011). The social brain in adolescence: evidence from functional magnetic resonance imaging and behavioural studies. Neuroscience Biobehavioral Review, 35, 16541664.Google Scholar
Bush, F., and McIlhaney, J. (2008). Hooked: new science on how casual sex is affecting our children. Chicago, IL: Northfield.Google Scholar
Butterworth, G., and Hopkins, B. (1988). Hand–mouth coordination in the newborn baby. British Journal of Developmental Psychology, 6, 303314.CrossRefGoogle Scholar
Cain, N., and Gradisar, M. (2010). Electronic media use and sleep in school-aged children and adolescents: a review. Sleep Medicine, 11, 735742.CrossRefGoogle ScholarPubMed
Cappuccio, F., Taggart, F., Kandala, N., Currie, A., Peile, E., Stranges, S., and Miller, M. (2008). Meta-analysis of short sleep duration and obesity in children and adults. Sleep, 31, 619626.Google Scholar
Capron, C., and Duyme, M. (1989). Assessment of effects of socioeconomic status on IQ in a full cross-fostering study. Nature, 340, 552554.CrossRefGoogle Scholar
Carey, S., and Diamond, R. (1977). From piecemeal to configurational representation of faces. Science, 195, 312314.Google Scholar
Carey, S., Diamond, R., and Woods, B. (1980). Development of face recognition – a maturational component? Developmental Psychology, 16, 257269.Google Scholar
Carlson, S., and Moses, L. (2001). Individual differences in inhibitory control and children's theory of mind. Child Development, 72, 10321053.Google Scholar
Carlson, S., Moses, L., and Claxton, L. (2004). Individual differences in executive functioning and theory of mind: an investigation of inhibitory control and planning ability. Journal of Experimental Child Psychology, 87, 299319.Google Scholar
Carpendale, J., and Lewis, C. (2004). Constructing an understanding of mind. The development of children's social understanding within social interaction. Behavioral and Brain Sciences, 27, 7996.CrossRefGoogle ScholarPubMed
Carper, R., and Courchesne, E. (2005). Localized enlargement of the frontal cortex in early autism. Biological Psychiatry, 57, 126133.Google Scholar
Carrell, S., Maghakian, T., and West, J. (2011). A's from Zzzz's? The causal effect of school start time on the academic achievement of adolescents. American Economic Journal: Economic Policy, 3, 6281.Google Scholar
Carskadon, M. (2011). Sleep in adolescents: the perfect storm. Pediatric Clinics of North America, 58, 637647.CrossRefGoogle ScholarPubMed
Casey, B.J. (2015). Beyond simple models of self-control to circuit-based accounts of adolescent behaviour. Annual Review of Psychology, 66, 295319.CrossRefGoogle Scholar
Casey, B.J., and Caudle, K. (2013). The teenage brain: self control. Current Directions in Psychological Science, 22, 8287.Google Scholar
Casey, B.J., Galván, A., and Hare, T. (2005). Changes in cerebral functional organization during cognitive development. Current Opinion in Neurobiology, 15, 239244.Google Scholar
Casey, B.J., Galván, A., and Somerville, L. (2015). Beyond simple models of adolescence to an integrated circuit-based account: a commentary. Developmental Cognitive Neuroscience, 17, 128130.CrossRefGoogle Scholar
Casey, B.J., Getz, S., and Galván, A. (2008). The adolescent brain. Developmental Review, 28, 6277.Google Scholar
Casey, B.J., Giedd, J., and Thomas, K. (2000). Structural and functional brain development and its relation to cognitive development. Biological Psychology, 54, 241257.CrossRefGoogle ScholarPubMed
Casey, B.J., Somerville, L., Gotlib, I., Ayduk, O., Franklin, N., Askren, M., Jonides, J., Berman, M.G., Wilson, N.L., Teslovich, T., Glover, G., Zayas, V., Mischel, W., and Shoda, Y. (2011). Behavioral and neural correlates of delay of gratification 40 years later. Proceedings of the National Academy of Sciences USA, 108, 14,99815,003.CrossRefGoogle ScholarPubMed
Casey, B.J., Tottenham, N., and Fossella, J. (2002). Clinical, imaging, lesion and genetic approaches toward a model of cognitive control. Developmental Psychobiology, 40, 237254.CrossRefGoogle Scholar
Casey, B.J., Trainor, R.J., Orendi, J.L., Schubert, A.B., Nystrom, L.E., Giedd, J.N., Castellanos, F.X., Haxby, J.V., Noll, D.C., Cohen, J.D. Forman, S.D., Dahl, R.E., and Rapoport, J.L. (1997). A developmental functional MRI study of prefrontal activation during performance of a Go-No-Go task. Journal of Cognitive Neuroscience, 9, 835847.CrossRefGoogle ScholarPubMed
Castellano, J., Roa, J., Luque, R., Dieguez, C., Aguilar, E., Pinilla, L., and Tena-Sempere, M. (2009). KiSS-1/kisspeptins and the metabolic control of reproduction: physiologic roles and putative physiopathological implications. Peptides, 30, 139145.CrossRefGoogle ScholarPubMed
Castellanos, F., Lee, P., Sharp, W., Jeffries, N., Greenstein, D., and Clasen, L. (2002). Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. Journal of the American Medical Association, 288, 17401748.CrossRefGoogle ScholarPubMed
Cavasos-Rehg, P., Krauss, M., and Spitznagel, E. (2012). Associations between selected state laws and teenagers’ drinking and driving behaviors. Alcohol and Clinical Experimental Research, 36, 16471652.Google Scholar
CDC (2011a). Nonfatal traumatic brain injuries related to sports and recreation activities among persons aged ≤19 years – United States, 2001–2009. Morbidity Mortality Weekly Report, 60, 13371342.Google Scholar
CDC (2011b). Tobacco use: targeting the nation's leading killer. Washington, DC: National Center for Chronic Disease Prevention and Health Promotion, Office of Smoking and Health.Google Scholar
CDC (2012). Web-based Injury Statistics Query and Reporting System (WISQARS). Retrieved from www.cdc.gov/injury/wisqars/index.html.Google Scholar
Chambers, R., Taylor, J., and Potenza, M. (2003). Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. American Journal of Psychiatry, 160, 10411052.CrossRefGoogle ScholarPubMed
Chein, J., Albert, D., O'Brien, L., Uckert, K., and Steinberg, L. (2011). Peers increase adolescent risk taking by enhancing activity in the brain's reward circuitry. Developmental Science, 14, F1F10.CrossRefGoogle ScholarPubMed
Chein, J., and Schneider, W. (2005). Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning. Cognitive Brain Research, 25, 607623.CrossRefGoogle ScholarPubMed
Chen, L., Baker, S., Braver, E., and Li, G. (2000). Carrying passengers as a risk factor for crashes fatal to 16- and 17-year-old drivers. Journal of the American Medical Association, 283, 15781582.CrossRefGoogle ScholarPubMed
Cheng, G., Gerlach, S., Libuda, L., Kranz, S., Gunther, A., Karaolis-Danckert, N., Kroke, A., and Buyken, A. (2010). Diet quality in childhood is prospectively associated with the timing of puberty but not with body composition at puberty onset. Journal of Nutrition, 140, 95102.Google Scholar
Cho, Y., Fromm, S., Guyer, A., Detloff, A., Pine, D., Fudge, J., and Ernst, M. (2013). Nucleus accumbens, thalamus and insula connectivity during incentive anticipation in typical adults and adolescents. Neuroimage, 66C, 508521.CrossRefGoogle ScholarPubMed
Choudhury, S., and McKinney, K. (2013). Digital media, the developing brain and the interpretive plasticity of neuroplasticity. Transcultural Psychiatry, 50, 192215.Google Scholar
Christakou, A., Brammer, M., and Rubia, A. (2011). Maturation of limbic corticostriatal activation and connectivity associated with developmental changes in temporal discounting. Neuroimage, 54, 13441354.Google Scholar
Chumlea, W., Schubert, C., Roche, A., Kulin, H., Lee, P., Himes, J., and Sun, S. (2003). Age at menarche and racial comparisons in US girls. Pediatrics, 111, 110113.CrossRefGoogle ScholarPubMed
Church, J., Petersen, S., and Schlaggar, B. (2010). The “Task B problem” and other considerations in developmental functional neuroimaging. Human Brain Mapping, 31, 852862.CrossRefGoogle Scholar
Cohen, J., and Servan-Schreiber, D. (1992). Context, cortex and dopamine: a connectionist approach to behavior and biology in schizophrenia. Psychological Review, 99, 4577.Google Scholar
Cohen, J.R., Asarnow, R.F., Sabb, F.W., Bilder, R.M., Bookheimer, S.Y., Knowlton, B.J., and Poldrack, R.A. (2010). A unique adolescent response to reward prediction errors. Nature Neuroscience, 13, 669671.CrossRefGoogle ScholarPubMed
Cohen-Gilbert, J., and Thomas, K. (2013). Inhibitory control during emotional distraction aross adolescence and early adulthood. Child Development, 84, 19541966.Google Scholar
Cohen Kadosh, K., Henson, R., Cohen Kadosh, R., Johnson, M., and Dick, F. (2010). Task-dependent activation of face-sensitive cortex: an fMRI adaptation study. Journal of Cognitive Neuroscience, 22, 903917.CrossRefGoogle ScholarPubMed
Cohen Kadosh, K., Johnson, M., Dick, F., Cohen Kadosh, R., and Blakemore, S. (2013). Effects of age, task performance, and structural brain development on face processing. Cerebral Cortex, 23, 16301642.Google Scholar
Constantinidis, C., and Klingberg, T. (2016). The neuroscience of working memory capacity and training. Nature Reviews Neurosciences, 17, 438449.CrossRefGoogle ScholarPubMed
Courchesne, E., Carper, R., and Akshoomoff, N. (2003). Evidence of brain outgrowth in the first year of life in autism. Journal of the American Medical Association, 290, 337344.CrossRefGoogle Scholar
Craig, A.D. (2009). How do you feel now? The anterior insula and human awareness. Nature Reviews Neuroscience, 10, 5970.CrossRefGoogle Scholar
Crone, E., and Dahl, R. (2012). Understanding adolescence as a period of social-affective engagement and goal flexibility. Nature Reviews Neuroscience, 13, 636650.CrossRefGoogle ScholarPubMed
Crone, E., Wendelken, C., Donohue, S., Van Leijenhorst, L., and Bunge, S. (2006). Neurocognitive development of the ability to manipulate information in working memory. Proceedings of the National Academy of Sciences USA, 103, 93159320.CrossRefGoogle ScholarPubMed
Crowley, S., Acebo, C., and Carskadon, M. (2007). Sleep, circadian rhythms, and delayed phase in adolescence. Sleep Medicine, 8, 602612.CrossRefGoogle ScholarPubMed
Crowley, S., and Carskadon, M. (2010). Modifications to weekend recovery sleep delay circadian phase in older adolescents. Chronobiology International, 27, 14691492.CrossRefGoogle ScholarPubMed
Csikszentmihalyi, M., Larson, R., and Prescott, S. (1977). The ecology of adolescent activity and experience. Journal of Youth and Adolescence, 6, 281294.Google Scholar
Curcio, G., Ferrara, M., and De Gennaro, L. (2006). Sleep loss, learning capacity and academic performance. Sleep Medicine Reviews, 10, 323337.CrossRefGoogle ScholarPubMed
Curry, A., Hafetz, J., Kallan, M., Winston, F., and Durbin, D. (2011). Prevalence of teen driver errors leading to serious motor vehicle crashes. Accident Analysis and Prevention, 43, 12851290.Google Scholar
Curry, A., Mirman, J., Kallan, M., Winston, F., and Durbin, D. (2012). Peer passengers: how do they affect teen crashes? Journal of Adolescent Health, 50, 588594.CrossRefGoogle ScholarPubMed
Cynader, M., and Mitchell, D. (1977). Monocular astigmatism effects on kitten visual cortex development. Nature, 270(5633), 177178.CrossRefGoogle ScholarPubMed
Dahl, R.E. (2004). Adolescent brain development: a period of vulnerabilities and opportunities. Annals of the New York Academy of Sciences, 1021, 122.CrossRefGoogle ScholarPubMed
Dalton, K., Nacewicz, B., Johnstone, T., Schaefer, H., Gernsbacher, M., Goldsmith, H., and Davidson, R. (2005). Gaze fixation and the neural circuitry of face processing in autism. Nature Neuroscience, 8, 519526.CrossRefGoogle ScholarPubMed
Danner, F., and Phillips, B. (2008). Adolescent sleep, school start times, and teen motor vehicle crashes. Journal of Clinical Sleep Medicine, 4, 533535.CrossRefGoogle ScholarPubMed
Dapretto, M., Davies, M., Pfeifer, J., Scott, A., Sigman, M., Bookheimer, S., and Iacoboni, M. (2006). Understanding emotions in others: mirror neuron dysfunction in children with autism spectrum disorder. Nature Neuroscience, 9, 2830.Google Scholar
Darki, F., and Klingberg, T. (2014). The role of fronto-parietal and fronto-striatal networks in the development of working memory: a longitudinal study. Cerebral Cortex, 25, 15871595.Google Scholar
Davidow, J.Y., Foerde, K., Galván, A., and Shohamy, D. (2016). An upside to reward sensitivity: the hippocampus supports enhanced reinforcement learning in adolescence. Neuron, 92, 9399.Google Scholar
Davidson, R., Kabat-Zinn, J., Schumacher, J., Rosenkranz, M., Muller, D., Santorelli, S., and Sheridan, J. (2003). Alterations in brain and immune function produced by mindfulness meditation. Psychosomatic Medicine, 65, 564570.Google Scholar
Davidson, R., and McEwen, B. (2012). Social influences on neuroplasticity: stress and interventions to promote well-being. Nature Neuroscience, 15, 689695.CrossRefGoogle ScholarPubMed
Davis, T., LaRocque, K., Mumford, J., Norman, K., Wagner, A., and Poldrack, R. (2014). What do differences between multi-voxel and univariate analysis mean? How subject-, voxel-, and trial-level variance impact fMRI analysis. Neuroimage, 97, 271283.CrossRefGoogle ScholarPubMed
Decety, J., and Svetlova, M. (2012). Putting together phylogenetic and ontogenetic perspectives on empathy. Developmental Cognitive Neuroscience, 2, 124.CrossRefGoogle ScholarPubMed
de Lange, F., Koers, A., Kalkman, J., Bleijenberg, G., Hagoort, P., van der Meer, J., and Toni, I. (2008). Increase in prefrontal cortical volume following cognitive behavioural therapy in patients with chronic fatigue syndrome. Brain, 131, 21722180.CrossRefGoogle ScholarPubMed
De Leonibus, C., Marcovecchio, M., Chiavaroli, V., de Giorgis, T., Chiarelli, F., and Mohn, A. (2014). Timing of puberty and physical growth in obese children: a longitudinal study in boys and girls. Pediatric Obesity, 9, 292299.CrossRefGoogle ScholarPubMed
Delcher, C., Johnson, R., and Maldonado-Molina, M. (2013). Driving after drinking among young adults of different race/ethnicities in the United States: unique risk factors in early adolescence? Journal of Adolescent Health, 52, 584591.Google Scholar
Delgado, M., Nearing, K., Ledoux, J., and Phelps, E. (2008). Neural circuitry underlying the regulation of conditioned fear and its relation to extinction. Neuron, 59, 829838.Google Scholar
Demerath, E., Towne, B., Chumlea, W., Sun, S., Czerwinski, S., Remsberg, K., and Siervogel, R. (2004). Recent decline in age at menarche: the Fels Longitudinal Study. American Journal of Human Biology, 16, 453457.Google Scholar
Demetriou, A., Christou, C., Spanoudis, G., and Platsidou, M. (2002). The development of mental processing: efficiency, working memory, and thinking. Monographs of the Society for Research in Child Development, 67, 1155.Google Scholar
Demos, K., Heatherton, T., and Kelley, W. (2012). Individual differences in nucleus accumbens activity to food and sexual images predict weight gain and sexual behavior. Journal of Neuroscience, 32, 55495552.Google Scholar
Deutsch, G., Dougherty, R., Bammer, R., Siok, W., Gabrieli, J., and Wandell, B. (2005). Chidren's reading performance is correlated with white matter structure measured by diffusion tensor imaging. Cortex, 41, 354363.CrossRefGoogle Scholar
Devlin, M., Walsh, B., Katz, J., Roose, S., Linkie, D., Wright, L., and Glassman, A. (1989). Hypothalamic-pituitary-gonadal function in anorexia nervosa and bulimia. Psychiatry Research, 28, 1124.CrossRefGoogle ScholarPubMed
Diamond, A. (2002). Normal development of prefrontal cortex from birth to young adulthood: cognitive functions, anatomy, and biochemistry. In Stuss, D. and Knight, R. (eds.), Principles of frontal lobe function (pp. 466503). Oxford: Oxford University Press.CrossRefGoogle Scholar
Diamond, A. (2012). Activities and programs that improve children's executive functions. Current Directions in Psychological Science, 21, 335341.Google Scholar
Diamond, A., Barnett, W., Thomas, J., and Munro, S. (2007). Preschool program improves cognitive control. Science, 318, 13871388.Google Scholar
Diamond, A., and Goldman-Rakic, P. (1989). Comparison of human infants and rhesus monkeys on Piaget's AB task: evidence for dependence on dorsolateral prefrontal cortex. Experimental Brain Research, 74, 2440.CrossRefGoogle ScholarPubMed
Diamond, A., Prevor, M., Callender, G., and Druin, D. (1997). Prefrontal cortex cognitive deficits in children treated early and continuously for PKU. Monographs of the Society for Research in Child Development, 62, 1208.CrossRefGoogle ScholarPubMed
Diamond, R., and Carey, S. (1977). Developmental changes in the representation of faces. Journal of Experimental Child Psychology, 23, 122.CrossRefGoogle ScholarPubMed
Diamond, R., Carey, S., and Back, K. (1983). Genetic influences on the development of spatial skills during early adolescence. Cognition, 13, 167185.CrossRefGoogle ScholarPubMed
Dickinson, M., Chekaluk, E., and Irwin, J. (2013). Visual attention in novice drivers: a lack of situation awareness. In Regan, M., Lee, J., and Victor, T. (eds.), Driver distraction and inattention: advances in resarch and countermeasure (pp. 277292). Burlington, VT: Ashgate.Google Scholar
Dollaghan, C., Campbell, T., Paradise, J., Feldman, H., Janosky, J., Pitcairn, D., and Kurs-Lasky, M. (1999). Maternal education and measures of early speech and language. Journal of Speech, Language and Hearing Research, 42, 14321443.Google Scholar
Doremus-Fitzwater, T.L., Varlinskaya, E.I., and Spear, L.P. (2010). Motivational systems in adolescence: possible implications for age differences in substance abuse and other risk-taking behaviors. Brain Cognition, 72, 114123.CrossRefGoogle ScholarPubMed
Dorn, L.D., Dahl, R.E., Woodward, H.R., and Biro, G. (2006). Defining the boundaries of early adolescence: a user's guide to assessing pubertal status and pubertal timing in research with adolescents. Applied Developmental Science, 10, 3056.CrossRefGoogle Scholar
Dosenbach, N., Nardos, B., Cohen, A., Fair, D., Power, J., Church, J., Nelson, S.M., Wig, G.S., Vogel, A.C., Lessov-Schlaggar, C.N., Barnes, K.A., Dubis, J.W., Feczko, E., Coalson, R.S., Pruett, J.R., Barch, D.M., Petersen, S.E., and Schlaggar, B.L. (2010). Prediction of individual brain maturity using fMRI. Science, 329, 13581361.CrossRefGoogle ScholarPubMed
Doucet, M., Guillemot, J., Lassonde, M., Gagne, J., Leclerc, C., and Lepore, F. (2005). Blind subjects process auditory spectral cues more efficiently than sighted individuals. Experimental Brain Research, 160, 194202.CrossRefGoogle ScholarPubMed
Douglas, L., Varlinskaya, E., and Spear, L. (2003). Novel-object place conditioning in adolescent and adult male and female rats: effects of social isolation. Physiology and Behavior, 80, 317325.CrossRefGoogle ScholarPubMed
Douglas, L., Varlinskaya, E., and Spear, L. (2004). Rewarding properties of social interactions in adolescent and adult male and female rats: impact of social versus isolate housing of subjects and partners. Developmental Psychobiology, 45, 153162.CrossRefGoogle ScholarPubMed
Doupe, A., and Kuhl, P. (2008). Birdsong and human speech: common themes and mechanisms. In Zeigler, H. and Marler, P. (eds.), Neuroscience of birdsong. Cambridge: Cambridge University Press.Google Scholar
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., and May, A. (2004). Neuroplasticity: changes in grey matter induced by training. Nature, 427, 311312.CrossRefGoogle ScholarPubMed
Duncan, G., Brooks-Gunn, J., and Klebanov, P. (1994). Economic deprivation and early childhood development. Child Development, 65(2 Spec. No.), 296318.CrossRefGoogle ScholarPubMed
Dunlop, S., and Romer, D. (2010). Adolescent and young adult crash risk: sensation seeking, substance use propensity, and substance use behaviors. Journal of Adolescent Health, 46, 9092.CrossRefGoogle Scholar
Durston, S., Davidson, M., Tottenham, N., Galván, A., Spicer, J., Fossella, J., and Casey, B. (2006). A shift from diffuse to focal cortical activity with development. Developmental Science, 9, 18.CrossRefGoogle ScholarPubMed
Durston, S., Mulder, M., Casey, B., Ziermans, T., and van Engeland, H. (2006). Activation in ventral prefrontal cortex is sensitive to genetic vulnerability for attention-deficit hyperactivity disorder. Biological Psychiatry, 60, 10621070.CrossRefGoogle ScholarPubMed
Eaton, D., Kann, L., Kinchen, S., Shanklin, S., Flint, K., Hawkins, J., Harris, W.A., Lowry, R., McManus, T., Chyen, D., Whittle, L., Lim, C., and Wechsler, H. (2012). Youth risk behavior surveillance – United States, 2011. MMWR Surveillance Summaries, 61, 1162.Google Scholar
Eisenberger, N., Lieberman, M., and Williams, K. (2003). Does rejection hurt? An fMRI study of social exclusion. Science, 302, 290292.CrossRefGoogle ScholarPubMed
Eisenberger, N.I., Taylor, S.E., Gable, S.L., Hilmert, C., and Lieberman, M. (2007). Neural pathways link social support to attenuated neuroendocrine stress responses. Neuroimage, 35, 16011612.Google Scholar
Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B., and Taub, E. (1995). Increased cortical representation of the fingers of the left hand in string players. Science, 270, 305307.Google Scholar
Elias, C. (2012). Leptin action in pubertal development: recent advances and unanswered questions. Trends in Endocrinology and Metabolism, 23, 915.CrossRefGoogle ScholarPubMed
Elkind, D., and Bowen, R. (1979). Imaginary audience behavior in children and adolescents. Developmental Psychology, 15, 3844.CrossRefGoogle Scholar
Ellis, B. (2004). Timing of pubertal maturation in girls: an integrated life history approach. Psychological Bulletin, 130, 920958.CrossRefGoogle ScholarPubMed
Ellis, B. (2013). The hypothalamic-pituitary-gonadal axis: a switch-controlled, condition-sensitive system in the regulation of life history strategies. Hormones and Behavior, 64, 215225.CrossRefGoogle ScholarPubMed
Erickson, K., Voss, M., Prakash, R., Basak, C., Szabo, A., Chaddock, L., Kim, J.S., Heo, S., Alves, H., White, S.M., Wojcicki, T.R., Mailey, E., Vieira, V.J., Martin, S.A., Pence, B.D., Woods, J.A., McAuley, E., and Kramer, A.F. (2011). Exercise training increases size of hippocampus and improves memory. Proceedings of the National Academy of Sciences USA, 108, 30173022.Google Scholar
Eriksen, B., and Eriksen, C. (1974). Effects of noise letters upon identification of a target letter in a non-search task. Perception and Psychophysics, 16, 143149.CrossRefGoogle Scholar
Erikson, K., Jones, B., and Beard, J. (2000). Iron deficiency alters dopamine transporter functioning in rat striatum. Journal of Nutrition, 130, 28312837.CrossRefGoogle ScholarPubMed
Ernst, M. (2014). The triadic model perspective for the study of adolescent motivated behavior. Brain and Cognition, 89, 104111.Google Scholar
Ernst, M., Nelson, E., Jazbec, S., McClure, E., Monk, C., Leibenluft, E., Blair, J., and Pine, D. (2005). Amygdala and nucleus accumbens in responses to receipt and omission of gains in adults and adolescents. Neuroimage, 25, 12791291.CrossRefGoogle ScholarPubMed
Ernst, M., Pine, D., and Hardin, M. (2006). Triadic model of the neurobiology of motivated behavior in adolescence. Psychological Medicine, 36, 299312.Google Scholar
Escalona, A., Field, T., Nadel, J., and Lundy, B. (2002). Brief report: imitation effects on children with autism. Journal of Autism Developmental Disorder, 32, 141144.Google Scholar
Esteban-Cornejo, I., Tejero-Gonzalez, C.M., Sallis, J.F., and Veiga, O.L. (2015). Physical activity and cognition in adolescents: a systematic review. Journal of Science and Medicine in Sport, 18, 534539.Google Scholar
Everitt, B., and Robbins, T. (2005). Neural systems of reinforcement for drug addiction: from actions to habits to compulsion. Nature Neuroscience, 8, 14811489.Google Scholar
Fair, D., Cohen, A., Dosenbach, N., Church, J., Miezin, F., Barch, D., Raichle, M.E., Petersen, S.E., and Schlaggar, B.L. (2008). The maturing architecture of the brain's default network. Proceedings of the National Academy of Sciences USA, 105, 40284032.CrossRefGoogle ScholarPubMed
Farooqi, I. (2002). Leptin and the onset of puberty: insights from rodent and human genetics. Seminars in Reproductive Medicine, 20, 139144.Google Scholar
Fehr, E., and Fischbacher, U. (2003). The nature of human altruism. Nature, 425, 785791.Google Scholar
Feinstein, J., Adolphs, R., Damasio, A., and Tranel, D. (2011). The human amygdala and the induction and experience of fear. Current Biology, 21, 3438.CrossRefGoogle ScholarPubMed
Fernandez-Fernandez, R., Martini, A., Navarro, V., Castellano, J., Dieguez, C., Aguilar, E., and Tena-Sempere, M. (2006). Novel signals for the integration of energy balance and reproduction. Molecular Cell Endocrinology, 254, 127132.CrossRefGoogle ScholarPubMed
Figner, B., Mackinlay, R., Wilkening, F., and Weber, E. (2009). Affective and deliberative processes in risky choice: age differences in risk taking in the Columbia Card Task. Journal of Experimental Psychology: Learning, Memory and Cognition, 35, 709730.Google Scholar
Finney, E., Fine, I., and Dobkins, K. (2001). Visual stimuli activate auditory cortex in the deaf. Nature Neuroscience, 4, 11711173.Google Scholar
Fiorillo, C., Tobler, P., and Schultz, W. (2003). Discrete coding of reward probability and uncertainty by dopamine neurons. Science, 299, 18981902.Google Scholar
Flor, H., Elbert, T., Knecht, S., Wienbruch, C., Pantev, C., Birbaumer, N., and Taub, E. (1995). Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation. Nature, 375, 482484.CrossRefGoogle ScholarPubMed
Forbes, E., and Dahl, R. (2010). Pubertal development and behavior: hormonal activation of social and motivational tendencies. Brain and Cognition, 72, 6672.CrossRefGoogle ScholarPubMed
Fox, M., Snyder, A., Vincent, J., Corbetta, M., Van Essen, D., and Raichle, M. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences USA, 102, 96739678.CrossRefGoogle ScholarPubMed
Fox, P., Raichle, M., Mintun, M., and Dence, C. (1988). Nonoxidative glucose consumption during focal physiologic neural activity. Science, 241, 462464.CrossRefGoogle ScholarPubMed
Fransson, P., Aden, U., Blennow, M., and Lagercrantz, H. (2011). The functional architecture of the infant brain as revealed by resting-state fMRI. Cerebral Cortex, 21, 145154.CrossRefGoogle ScholarPubMed
Fredriksen, K., Rhodes, J., Reddy, R., and Way, N. (2004). Sleepless in Chicago: tracking the effects of adolescent sleep loss during the middle school years. Child Development, 75, 8495.Google Scholar
Freedman, D., Khan, L., Serdula, M., Dietz, W., Srinivasan, S., and Berenson, G. (2002). Relation of age at menarche to race, time period, and anthropometric dimensions: the Bogalusa Heart Study. Pediatrics, 110, e43.Google Scholar
Freud, A. (1966–1980). The writings of Anna Freud, 8 vols. New York: Indiana University of Pennsylvania: vol. 4, Indications for child analysis and other papers (1945–1956) (1946); vol. 5, Research at the Hampstead Child-Therapy Clinic and other papers (1956–1965) (1958); vol. 7, Problems of psychoanalytic training, diagnosis, and the technique of therapy (1966–1970) (1968).Google Scholar
Friedman, N., Haberstick, B., Willcutt, E., Miyake, A., Young, S., and Corley, R. (2007). Greater attention problems during childhood predict poorer executive functioning in late adolescence. Psychological Science, 18, 893900.CrossRefGoogle ScholarPubMed
Friemel, C., Spanagel, R., and Schneider, M. (2010). Reward sensitivity for a palatable food reward peaks during pubertal developmental in rats. Frontiers in Behavioral Neuroscience, 4, 110.Google ScholarPubMed
Frisch, R., and Revelle, R. (1970). Height and weight at menarche and a hypothesis of critical body weights and adolescent events. Science, 169, 397399.Google Scholar
Friston, K., Worsley, K., Frackowiak, R., Mazziotta, J., and Evans, A. (1994). Assessing the significance of focal activations using their spatial extent. Human Brain Mapping, 1, 210220.Google Scholar
Frith, C. (2008). Social cognition. Philosophical Transactions of the Royal Society of London B Biological Sciences, 363(1499), 20332039.Google Scholar
Fuster, J. (2001). The prefrontal cortex – an update: time is of the essence. Neuron, 30, 319333.Google Scholar
Fuster, J., and Alexander, G. (1971). Neuron activity related to short-term memory. Science, 173, 652654.CrossRefGoogle ScholarPubMed
Galani, R., Coutureau, E., and Kelche, C. (1998). Effects of enriched postoperative housing conditions on spatial memory deficits in rats with selective lesions of either the hippocampus, subiculum or entorhinal cortex. Restorative Neurology and Neurosciences, 13, 173184.Google ScholarPubMed
Galván, A (2013a). Sensitivity to reward in adolescence. Current Directions in Psychological Science, 22, 100105.CrossRefGoogle Scholar
Galván, A. (2013b). The teenage brain: sensitivity to rewards. Current Directions in Psychological Science, 22, 8893.CrossRefGoogle Scholar
Galván, A. (2014). Insights about adolescent behavior, plasticity and policy from neuroscience research. Neuron, 83, 262265.Google Scholar
Galván, A., Hare, T., Parra, C., Penn, J., Voss, H., Glover, G., and Casey, B. (2006). Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk-taking behavior in adolescents. Journal of Neuroscience, 26, 68856892.Google Scholar
Galván, A., Hare, T., Voss, H., Glover, G., and Casey, B. (2007). Risk-taking and the adolescent brain: who is at risk? Developmental Science, 10, F8F14.Google Scholar
Galván, A., and McGlennen, K. (2013). Enhanced striatal sensitivity to aversive reinforcement in adolescents versus adults. Journal of Cognitive Neuroscience, 25, 284296.CrossRefGoogle ScholarPubMed
Galván, A., Van Leijenhorst, L., and McGlennen, K. (2012). Considerations for imaging the adolescent brain. Developmental Cognitive Neuroscience, 2, 293302.CrossRefGoogle ScholarPubMed
Gardner, M., and Steinberg, L. (2005). Peer influence on risk-taking, risk preference, and risky decision-making in adolescence and adulthood: an experimental study. Developmental Psychology, 4, 625635.CrossRefGoogle Scholar
Gauthier, I., and Nelson, C.A. (2001). The development of face expertise. Current Opinion in Neurobiology, 11, 219224.CrossRefGoogle ScholarPubMed
Gee, D.G., Humphreys, K.L., Flannery, J., Goff, B., Telzer, E.H., Shapiro, M., Hare, T.A., Bookheimer, S.Y., and Tottenham, N. (2013). A developmental shift from positive to negative connectivity in human amygdala-prefrontal circuitry. Journal of Neuroscience, 33, 45844593.CrossRefGoogle ScholarPubMed
Geier, C., and Luna, B. (2009). The maturation of incentive processing and cognitive control. Pharmacology, Biochemistry and Behavior, 93, 212221.Google Scholar
Geier, C., Terwilliger, R., Teslovich, T., Velanova, K., and Luna, B. (2010). Immaturities in reward processing and its influence on inhibitory control in adolescence. Cerebral Cortex, 20, 16131629.Google Scholar
Giedd, J., Castellanos, F., Casey, B., Kozuch, P., King, A.C., Hamburger, S.D., and Rapoport, J.L. (1994). Quantitative morphology of the corpus callosum in attention deficit hyperactivity disorder. American Journal of Psychiatry, 151, 665669.Google ScholarPubMed
Giedd, J., Raznahan, A., Alexander-Bloch, A., Schmitt, E., Gogtay, N., and Rapoport, J. (2015). Child psychiatry branch of the National Institute of Mental Health longitudinal structural magnetic resonance imaging study of human brain development. Neuropsychopharmacology, 40, 4349.CrossRefGoogle ScholarPubMed
Gillen-O'Neel, C., Huynh, V., and Fuligni, A. (2013). To study or to sleep? The academic costs of extra studying and sleep loss. Child Development, 84, 133142.CrossRefGoogle ScholarPubMed
Goddings, A.L., Burnett Hayes, S., Bird, G., Viner, R.M., and Blakemore, S.J. (2012). The relationship between puberty and social emotion processing. Developmental Science, 15, 801811.CrossRefGoogle ScholarPubMed
Goddings, A.L., Mills, K.L., Clasen, L.S., Giedd, J.N., Viner, R.M., and Blakemore, S.J. (2014). The influence of puberty on subcortical brain development. Neuroimage, 88, 242251.Google Scholar
Gogtay, N., and Rapoport, J. (2008). Childhood-onset schizophrenia: insights from neuroimaging studies. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 11201124.Google Scholar
Gohlke, J., Griffith, W., and Faustman, E. (2007). Computational models of neocortical neuronogenesis and programmed cell death in the developing mouse, monkey, and human. Cerebral Cortex, 17, 24332442.CrossRefGoogle ScholarPubMed
Golarai, G., Ghahremani, D.G., Whitfield-Gabrieli, S., Reiss, A., Eberhardt, J.L., Gabrieli, J.D., and Grill-Spector, K. (2007). Differential development of high-level visual cortex correlates with category-specific recognition memory. Nature Neuroscience, 10, 512522.CrossRefGoogle ScholarPubMed
Golarai, G., Grill-Spector, K., and Reiss, A. (2006). Autism and the development of face processing. Clinical Neuroscience Research, 6, 145160.CrossRefGoogle ScholarPubMed
Golarai, G., Liberman, A., Yoon, J.M., and Grill-Spector, K. (2010). Differential development of the ventral visual cortex extends through adolescence. Frontiers in Human Neuroscience, 3, 80.Google ScholarPubMed
Goldman-Rakic, P. (1996). The prefrontal landscape: implications of functional architecture for understanding human mentation and the central executive. Philosophical Transactions of the Royal Society B, 351, 14451453.Google ScholarPubMed
Goldenberg, D., and Galván, A. (2015). The use of functional and effective connectivity techniques to understand the developing brain. Developmental Cognitive Neuroscience, 12, 155164.CrossRefGoogle ScholarPubMed
Goldman-Rakic, P. (1996). The prefrontal landscape: implications of functional architecture for understanding human mentation and the central executive. Philosophical Transactions of the Royal Society B, 351, 14451453.Google Scholar
Gomez, J., Barnett, M.A., Natu, V., Mezer, A., Palomero-Gallagher, N., Weiner, K.S., Amunts, K., Zilles, K., and Grill-Spector, K. (2017). Microstructural proliferation in human cortex is coupled with the development of face processing. Science, 355, 6871.Google Scholar
Gopnik, A., and Wellman, H. (2012). Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory. Psychological Bulletin, 138, 10851108.CrossRefGoogle ScholarPubMed
Gordon, R. (1992). The simulation theory: objections and misconceptions. Mind and Language, 7, 1134.CrossRefGoogle Scholar
Gould, E., Reeves, A.J., Graziano, M.S., and Gross, C.G. (1999). Neurogenesis in the neocortex of adult primates. Science, 286, 548552.CrossRefGoogle ScholarPubMed
Goyal, M., Hawrylycz, M., Miller, J., Snyder, A., and Raichle, M. (2014). Aerobic glycolysis in the human brain is associated with development and neotenous gene expression. Cell Metabolism, 19, 4957.Google Scholar
Graber, J. (2013). Pubertal timing and the development of psychopathology in adolescence and beyond. Hormones and Behavior, 64, 262269.CrossRefGoogle ScholarPubMed
Graber, J., Nichols, T., and Brooks-Gunn, J. (2010). Putting pubertal timing in developmental context: implications for prevention. Developmental Psychobiology, 52, 254262.CrossRefGoogle ScholarPubMed
Graber, J., Seeley, J., Brooks-Gunn, J., and Lewinsohn, P. (2004). Is pubertal timing associated with psychopathology in young adulthood? Journal of the American Academy of Child and Adolescent Psychiatry, 43, 718726.Google Scholar
Greenough, W., Black, J., and Wallace, C. (1987). Experience and brain development. Child Development, 58, 539559.Google Scholar
Greenough, W., and Volkmar, F. (1973). Pattern of dendritic branching in occipital cortex of rats reared in complex environments. Experimental Neurology, 40, 491504.CrossRefGoogle ScholarPubMed
Greenough, W., Volkmar, F., and Juraska, J. (1973). Effects of rearing complexity on dendritic branching in frontolateral and temporal cortex of the rat. Experimental Neurology, 41, 371378.CrossRefGoogle ScholarPubMed
Greenough, W., Withers, G., and Anderson, B. (1992). Experience-dependent synaptogenesis as a plausible memory mechanism. In Gormezano, I. and Vasserman, E. (eds.), Learning and memory: the behavioral and biological substrates (pp. 209229). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Gregersen, N., and Bjurulf, P. (1996). Young novice drivers: towards a model of their accident involvement. Accident Analysis and Prevention, 28, 229241.Google Scholar
Gregory, A., and Sadeh, A. (2012). Sleep, emotional and behavioral difficulties in children and adolescents. Sleep Medicine Reviews, 16, 129136.Google Scholar
Grelotti, D., Gauthier, I., and Schultz, R. (2001). Social interest and the development of cortical face specialization: what autism teaches us about face processing. Developmental Psychobiology, 40, 213225.Google Scholar
Grisso, T., Steinberg, L., Woolard, J., Cauffman, E., Scott, E., Graham, S., Lexcen, F., Reppucci, N.D., and Schwartz, R. (2003). Juveniles’ competence to stand trial: a comparison of adolescents’ and adults’ capacities as trial defendants. Law and Human Behavior, 27, 333363.Google Scholar
Groman, S., James, A., Seu, E., Tran, S., Clark, T., Harpster, S., and Jentsch, J. (2014). In the blink of an eye: relating positive-feedback sensitivity to striatal dopamine D2-like receptors through blink rate. Journal of Neuroscience, 34, 14,443–14,454.Google Scholar
Grossmann, T., and Johnson, M. (2007). The development of the social brain in human infancy. European Journal of Neuroscience, 25, 909919.Google Scholar
Guroglu, B., van den Bos, W., and Crone, E. (2014). Sharing and giving across adolescence: an experimental study examining the development of prosocial behavior. Frontiers in Psychology, 5, 291297.Google Scholar
Guttmacher, (2014). State policies in brief: sex and HIV education. Guttmacher Institute. Retrieved from www.guttmacher.org/statecenter/spibs/spib_SE.pdf.Google Scholar
Guye, M., Bartolomei, F., and Ranjeva, J. (2008). Imaging structural and functional connectivity: towards a unified definition of human brain organization? Current Opinion in Neurology, 21, 393403.CrossRefGoogle ScholarPubMed
Guyer, A., Choate, V., Pine, D., and Nelson, E. (2012). Neural circuitry underlying affective response to peer feedback in adolescence. Social Cognitive and Affective Neuroscience, 7, 8192.CrossRefGoogle ScholarPubMed
Guyer, A., McClure-Tone, E., Shiffrin, N.D., Pine, D., and Nelson, E. (2009). Probing the neural correlates of anticipated peer evaluation in adolescence. Child Development, 80, 10001015.CrossRefGoogle ScholarPubMed
Guyer, A., Monk, C., McClure-Tone, E., Nelson, E., Roberson-Nay, R., Adler, A., Fromm, S.J., Leibenluft, E., Pine, D.S., and Ernst, M. (2008). A developmental examination of amygdala response to facial expressions. Journal of Cognitive Neuroscience, 20, 15651582.Google Scholar
Gweon, H., Dodell-Feder, D., Bedny, M., and Saxe, R. (2013). Theory of mind performance in children correlates with functional specialization of a brain region for thinking about thoughts. Child Development, 83, 18531868.Google Scholar
Haacke, E., Cheng, N., House, M., Liu, Q., Neelavalli, J., Ogg, R., and Obenaus, A. (2005). Imaging iron stores in the brain using magnetic resonance imaging. Magnetic Resonance Imaging, 23, 125.Google Scholar
Haber, S. (2011). Neuroanatomy of reward: a view from the ventral striatum. In Gottfried, J. (ed.), Neurobiology of sensation and reward (pp. 235262). Boca Raton, FL: CRC Press.Google ScholarPubMed
Haber, S., and Knutson, B. (2010). The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology, 35, 426.CrossRefGoogle ScholarPubMed
Hackman, D., Farah, M., and Meaney, M. (2010). Socioeconomic status and the brain: mechanistic insights from human and animal research. Nature Reviews Neuroscience, 11, 651659.Google Scholar
Hadjikhani, N., Joseph, R., Snyder, J., and Tager-Flusberg, H. (2006). Anatomical differences in the mirror neuron system and social cognition network in autism. Cerebral Cortex, 16, 12761282.Google Scholar
Hagenauer, M., and Lee, T. (2013). Adolescent sleep patterns in humans and laboratory animals. Hormones and Behavior, 64, 270279.CrossRefGoogle ScholarPubMed
Hall, G.S. (1904). Adolescence: its psychology and its relations to physiology, anthropology, sociology, sex, crime, religion, and education, vols. I and II. New York: D. Appleton & Co.Google Scholar
Halverson, H. (1933). The acquisition of skill in infancy. Journal of Genetic Psychology, 43, 348.Google Scholar
Hare, T., Tottenham, N., Galván, A., Voss, H., Glover, G., and Casey, B. (2008). Biological substrates of emotional reactivity and regulation in adolescence during an emotional go-nogo task. Biological Psychiatry, 63, 927934.CrossRefGoogle ScholarPubMed
Hariri, A., Mattay, V., Tessitore, A., Fera, F., and Weinberger, D. (2003). Neocortical modulation of the amygdala response to fearful stimuli. Biological Psychiatry, 53, 494501.CrossRefGoogle ScholarPubMed
Harlan, W.R., Harlan, E.A., and Grillo, G.P. (1980). Secondary sex characteristics of girls 12 to 17 years of age: the U.S. Health Examination Survey. Journal of Pediatrics, 96, 10741078.Google ScholarPubMed
Harrison, E., and Fillmore, M. (2011). Alcohol and distraction interact to impair driving performance. Drug and Alcohol Dependence, 117, 3137.Google Scholar
Hart, B., and Risley, T. (2003). The early catastrophe: the 30 million word gap by age 3. American Educator, Spring, 49.Google Scholar
Harter, S. (1999). The construction of the self: a developmental perspective. New York: The Guilford Press.Google Scholar
Hartley, C., Fischl, B., and Phelps, E. (2011). Brain structure correlates of individual differences in the acquisition and inhibition of conditioned fear. Cerebral Cortex, 21, 19541962.Google Scholar
Hartman, R., and Huestis, M. (2013). Cannabis effects on driving skills. Clinical Chemistry, 59, 478492.CrossRefGoogle ScholarPubMed
Haxby, J., Gobbini, M., Furey, M., Ishai, A., Schouten, J., and Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 24252430.Google Scholar
Haxby, J., Grady, C., Horwitz, B., Ungerleider, L., Mishkin, M., Carson, R., Herscovitch, P., Schapiro, M.B., and Rapoport, S.I. (1991). Dissociation of object and spatial visual processing pathways in human extrastriate cortex. Proceedings of the National Academy of Sciences USA, 88, 16211625.Google Scholar
Haxby, J., Hoffman, E., and Gobbini, M. (2000). The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223233.CrossRefGoogle ScholarPubMed
Hebb, D. (ed.) (1949). The organisation of behaviour: a neuropsychlogical theory. New York: John Wiley and Sons.Google Scholar
Heimer, L., De Olmos, J., Alheid, G., Person, J., Sakamoto, N., Shinoda, K., Marksteiner, J., and Switzer, R.C. (1999). The human basal forebrain. Part II. In Bloom, F., Bjorkland, A. and Hokfelt, T. (eds.), Handbook of chemical neuroanatomy (pp. 57226). Amsterdam: Elsevier.Google Scholar
Herculano-Houzel, S. (2009). The human brain in numbers: a linearly scaled-up primate brain: Frontiers in Human Neuroscience, 9, 31.Google Scholar
Herman-Giddens, M., Slora, E., Wasserman, R., Bourdony, C., Bhapkar, M., Koch, G., and Hasemeier, C. (1997). Secondary sexual characteristics and menses in young girls seen in office practice: a study from the Pediatric Research in Office Settings network. Pediatrics, 99, 505512.CrossRefGoogle Scholar
Herman-Giddens, M., Steffes, J., Harris, D., Slora, E., Hussey, M., Dowshen, S., and Reiter, E. (2012). Secondary sexual characteristics in boys: data from the Pediatric Research in Office Settings Network. Pediatrics, 130, e1058e1068.Google Scholar
Herman-Giddens, M., Wang, L., and Koch, G. (2001). Secondary sexual characteristics in boys: estimates from the National Health and Nutrition Examination Survey III, 1988–1994. Archives of Pediatrics and Adolescent Medicine, 155, 10221028.Google Scholar
Herting, M.M., Gautam, P., Spielberg, J.M., Kan, E., Dahl, R.E., and Sowell, E.R. (2014). The role of testosterone and estradiol in brain volume changes across adolescence: a longitudinal structural MRI study. Human Brain Mapping, 35, 56335645.Google Scholar
Hillman, C., Erickson, K., and Kramer, A. (2008). Be smart, exercise your heart: exercise effects on brain and cognition. Nature Reviews Neuroscience, 9, 5865.CrossRefGoogle ScholarPubMed
Hoffman, E.A., and Haxby, J.V. (2000). Distinct representations of eye gaze and identity in the distributed human neural system for face perception. Nature Neuroscience, 3, 8084.CrossRefGoogle ScholarPubMed
Huttenlocher, P. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28, 517527.CrossRefGoogle ScholarPubMed
Huttenlocher, P., and Dabholkar, A. (1997). Regional difference in synaptogenesis in human cerebral cortex. Journal of Comparative Neurology, 387, 167178.Google Scholar
Hwang, K., Velanova, K., and Luna, B. (2010). Strengthening of top-down frontal cognitive control networks underlying the development of inhibitory control: an fMRI effective connectivity study. Journal of Neuroscience, 30, 15,535–15,545.Google Scholar
Hyde, K., Lerch, J., Norton, A., Forgeard, M., Winner, E., Evans, A., and Schlaug, G. (2009). Musical training shapes structural brain development. Journal of Neuroscience, 29, 30193025.Google Scholar
Hymovitch, B. (1952). The effects of experimental variations on problem solving in the rat. Journal of Comparative Physiology and Psychology, 45, 313321.Google Scholar
James, W. (1890). The principles of psychology. New York: Henry Holt and Company.Google Scholar
Jansons, K., and Alexander, D. (2003). Persistent Angular Structure: new insights from diffusion MRI data. Dummy version. Information Processing in Medical Imaging, 18, 672683.Google Scholar
Jarcho, J., Benson, B., Plate, R., Guyer, A., Detloff, A., Pine, D., and Ernst, M. (2012). Developmental effects of decision-making on sensitivity to reward: an fMRI study. Developmental Cognitive Neuroscience, 2, 437447.CrossRefGoogle ScholarPubMed
Jensen, J., Helpern, J., Ramani, A., Lu, H., and Kaczynski, K. (2005). Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magnetic Resonance Medicine, 53, 14321440.Google Scholar
Johnson, M. (2005). Subcortical face processing. Nature Reviews Neuroscience, 6, 766774.Google Scholar
Johnson, M. (2011). Interactive specialization: a domain-general framework for human functional brain development? Developmental Cognitive Neuroscience, 1, 721.CrossRefGoogle ScholarPubMed
Johnson, M., Dziurawiec, S., Ellis, H., and Morton, J. (1991). Newborns’ preferential tracking of face-like stimuli and its subsequent decline. Cognition, 40, 119.Google Scholar
Johnson, S.B., Riis, J.L., and Noble, K.G. (2016). State of the art review: poverty and the developing brain. Pediatrics, 137, 116.Google Scholar
Johnston, M. (2009). Plasticity in the developing brain: implications for rehabilitation. Developmental Disabilities Research Review, 15, 94101.Google Scholar
Juraska, J., Fitch, J., Henderson, C., and Rivers, N. (1985). Sex differences in the dendritic branching of dentate granule cells following differential experience. Brain Research, 333, 7380.CrossRefGoogle ScholarPubMed
Kang, H., Burgund, E., Lugar, H., Petersen, S., and Schlaggar, B. (2003). Comparison of functional activation foci in children and adults using a common stereotactic space. Neuroimage, 19, 1628.CrossRefGoogle ScholarPubMed
Kanold, P. (2009). Subplate neurons: crucial regulators of cortical development and plasticity. Frontiers in Neuroanatomy, 3, 19.CrossRefGoogle ScholarPubMed
Kanwisher, N., McDermott, J., and Chun, M. (1997). The fusiform face area: a module in human extrastriate cortex specialized for face perception. Journal of Neuroscience, 17, 43024311.Google Scholar
Karni, A., Meyer, G., Jezzard, P., Adams, M., Turner, R., and Ungerleider, L. (1995). Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature, 377, 155158.Google ScholarPubMed
Karson, C. (1983). Spontaneous eye-blink rates and dopaminergic systems. Brain, 106, 643653.Google Scholar
Kawashima, R., Sugiura, M., Kato, T., Nakamura, A., Hatano, K., Ito, K., Kukuda, H., Kojima, S., and Nakamura, K. (1999). The human amygdala plays an important role in gaze monitoring. A PET study. Brain, 122, 779783.Google Scholar
Keating, D. (2007). Understanding adolescent development: implications for driving safety. Journal of Safety Research, 38, 147157.Google Scholar
Kelly, A., Di Martino, A., Uddin, L., Shehzad, Z., Gee, D., Reiss, P., and Milham, M. (2009). Development of anterior cingulate functional connectivity from late childhood to early adulthood. Cerebral Cortex, 19, 640657.CrossRefGoogle ScholarPubMed
Kessler, R., Berglund, P., Demler, O., Jin, R., Merikangas, K., and Walters, E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 593602.Google Scholar
Killgore, W., and Yurgelun-Todd, D. (2007). Unconscious processing of facial affect in children and adolescents. Social Neuroscience, 2, 2847.Google Scholar
Kim, H., Somerville, L., Johnstone, T., Polis, S., Alexander, A.L., Shin, L.M., and Whalen, P.J. (2004). Contextual modulation of amygdala responsivity to surprised faces. Journal of Cognitive Neuroscience, 16, 17301745.CrossRefGoogle ScholarPubMed
Kim, M., Loucks, R., Palmer, A., Brown, A., Solomon, K., Marchante, A., and Whalen, P. (2011). The structural and functional connectivity of the amygdala: from normal emotion to pathological anxiety. Behavior Brain Research, 223, 403410.Google Scholar
Ki-moon, B. (2013). Five-year action agenda: Office of the Secretary General's Envoy on Youth. New York: United Nations.Google Scholar
Kirkham, N., Slemmer, J., and Johnson, S. (2002). Visual statistical learning in infancy: evidence for a domain general learning mechanism. Cognition, 83, B35B42.Google Scholar
Kishiyama, M., Boyce, W., Jimenez, A., Perry, L., and Knight, R. (2009). Socioeconomic disparities affect prefrontal function in children. Journal of Cognitive Neuroscience, 21, 11061115.CrossRefGoogle ScholarPubMed
Klapwijk, E., Goddings, A., Burnett Heyes, S., Bird, G., Viner, R., and Blakemore, S. (2013). Increased functional connectivity with puberty in the mentalising network involved in social emotion processing. Hormones and Behavior, 64, 314322.Google Scholar
Klapwijk, E.T., Peters, S., Vermeiren, R.R., and Lelieveld, G.J. (2013). Emotional reactions of peers influence decisions about fairness in adolescence. Frontiers in Human Neuroscience, 7, 745.Google Scholar
Klingberg, T., Forssberg, H., and Westerberg, H. (2002). Increased brain activity in frontal and parietal cortex underlies the development of visuospatial working memory capacity during childhood. Journal of Cognitive Neuroscience, 14, 110.CrossRefGoogle ScholarPubMed
Knutson, K., and Lauderdale, D. (2009). Sociodemographic and behavioral predictors of bed time and wake time among US adolescents aged 15 to 17 years. Journal of Pediatrics, 154, 426430.CrossRefGoogle ScholarPubMed
Koch, R., and Wenz, E. (1987). Phenylketonuria. Annual Review of Nutrition, 7, 117135.Google Scholar
Koenderink, M., Ulyings, H., and Mrzljiak, L. (1994). Postnatal maturation of the layer III pyramidal neurons in the human prefrontal cortex: a quantitative Golgi analysis. Brain Research, 653, 173182.Google Scholar
Koolschijn, P., Schel, M., de Rooij, M., Rombouts, S., and Crone, E. (2011). A three-year longitudinal functional magnetic resonance imaging study of performance monitoring and test–retest reliability from childhood to early adulthood. Journal of Neuroscience, 31, 42044212.Google Scholar
Krain, A., Gotimer, K., Hefton, S., Ernst, M., Castellanos, F., Pine, D., and Milham, M. (2008). A functional magnetic resonance imaging investigation of uncertainty in adolescents with anxiety disorders. Biological Psychiatry, 63, 563568.CrossRefGoogle ScholarPubMed
Krain, A., Hefton, S., Pine, D., Ernst, M., Castellanos, F., Klein, R., and Milham, M. (2006). An fMRI examination of developmental differences in the neural correlates of uncertainty and decision making. Journal of Child Psychology and Psychiatry, 47, 10231030.Google Scholar
Kuhnen, C., and Knutson, B. (2005). The neural basis of financial risk taking. Neuron, 47, 763770.CrossRefGoogle ScholarPubMed
Kwon, H., Reiss, A., and Menon, V. (2002). Neural basis of protracted developmental changes in visuo-spatial working memory. Proceedings of the National Academy of Sciences USA, 99, 13,33613,341.CrossRefGoogle ScholarPubMed
LaBar, K., and Cabeza, R. (2006). Cognitive neuroscience of emotional memory. Nature Reviews Neuroscience, 7, 5464.CrossRefGoogle ScholarPubMed
Ladouceur, C.D., Peper, J.S., Crone, E.A., and Dahl, R.E. (2012). White matter development in adolescence: the influence of puberty and implications for affective disorders. Developmental Cognitive Neuroscience, 2, 3654.Google Scholar
Lakes, K., and Hoyt, W. (2004). Promoting self-regulation through school-based martial arts training. Applied Developmental Psychology, 25, 283302.CrossRefGoogle Scholar
Langdell, T. (1978). Recognition of faces: an approach to the study of autism. Journal of Child Psychology and Psychiatry, 19, 255268.CrossRefGoogle Scholar
Larsen, B., and Luna, B. (2015). In vivo evidence of neurophysiological maturation of the human adolescent striatum. Developmental Cognitive Neuroscience, 12, 7485.Google Scholar
Larson, R., Richards, M., Moneta, G., Holmbeck, G., and Duckett, E. (1996). Changes in adolescents’ daily interactions with their families from ages 10 to 18: disengagement and transformation. Developmental Psychology, 32, 744754.Google Scholar
Laviola, G., Macri, S., Morley-Fletcher, S., and Adriani, W. (2003). Abstract risk-taking behavior in adolescent mice: psychobiological determinants and early epigenetic influence. Neuroscience and Biobehavioral Reviews, 27, 1931.Google Scholar
Laviola, G., Pasucci, T., and Pieretti, S. (2001). Striatal dopamine sensitization to D-amphetamine in periadolescent but not in adult rats. Pharmacology, Biochemistry and Behavior, 68, 115124.CrossRefGoogle ScholarPubMed
Lawrence, N., Hinton, E., Parkinson, J., and Lawrence, A. (2012). Nucleus accumbens response to food cues predicts subsequent snack consumption in women and increased body mass index in those with reduced self-control. Neuroimage, 63, 415422.CrossRefGoogle ScholarPubMed
Lazarus, R.S. (1963). Personality and adjustment. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Leary, M., and Tangney, J. (eds.) (2003). The self as an organizing construct in the behavioral and social sciences. In Handbook of self and identity (pp. 314). New York: The Guilford Press.Google Scholar
Lebel, C., Gee, M., Carmicioli, R., Wieler, M., Martin, W., and Beaulieu, C. (2012). Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage, 60, 340352.CrossRefGoogle ScholarPubMed
Le Bihan, D. (1995). Diffusion, perfusion and functional magnetic resonance imaging. Journal des maladies vasculaires, 20, 209214.Google ScholarPubMed
Lee, H.K., and Whitt, J.L. (2015). Cross-modal synaptic plasticity in adult primary sensory cortices. Current Opinion in Neurobiology, 35, 119126.CrossRefGoogle ScholarPubMed
Leggio, M., Mandolesi, L., Federico, F., Spirito, F., Ricci, B., Gelfo, F., and Petrosini, L. (2005). Environmental enrichment promotes improved spatial abilities and enhanced dendritic growth in the rat. Behavior Brain Research, 163, 7890.CrossRefGoogle ScholarPubMed
Le Grand, R., Mondloch, C., Maurer, D., and Brent, H. (2003). Expert face processing requires visual input to the right hemisphere during infancy. Nature Neuroscience, 6, 11081112.CrossRefGoogle Scholar
Lenhart, A., Ling, R., Campbell, S., and Purcell, K. (2010). Teens and mobile phones. Retrieved from http://pewinternet.org/Reports/2010/Teens-and- Mobile-Phones.aspx.Google Scholar
Lenroot, R., Gogtay, N., Greenstein, D., Wells, E., Wallace, G., Clasen, L., and Giedd, J. (2007). Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage, 36, 10651073.CrossRefGoogle ScholarPubMed
Leslie, A., Friedman, O., and German, T. (2004). Core mechanisms in “theory of mind.” Trends in Cognitive Sciences, 8, 528533.Google Scholar
Lessard, N., Pare, M., Lepore, F., and Lassonde, M. (1998). Early-blind human subjects localize sound sources better than sighted subjects. Nature, 395, 278280.Google Scholar
LeVay, S., Wiesel, T., and Hubel, D. (1980). The development of ocular dominance columns in normal and visually deprived monkeys. Journal of Comparative Neurology, 191, 151.CrossRefGoogle ScholarPubMed
Levelt, C., and Hübener, M. (2012). Critical-period plasticity in the visual cortex. Annual Review of Neuroscience, 35, 309330.Google Scholar
Lewis, M., and Carmody, D. (2008). Self-representation and brain development. Developmental Psychology, 44, 13291334.CrossRefGoogle ScholarPubMed
Lind, S., and Bowler, D. (2008). Episodic memory and autonoetic consciousness in autistic spectrum disorders: the roles of self-awareness, representational abilities and temporal cognition. Memory in Autism: Theory and Evidence, 48, 166187.Google Scholar
Liston, C., McEwen, B.S., and Casey, B. (2009). Psychosocial stress reversibly dirupts prefrontal processing and attentional control. Proceedings of the National Academy of Sciences USA, 106, 912917.CrossRefGoogle ScholarPubMed
Liszkowski, U., Carpenter, M., Striano, T., and Tomasello, M. (2006). Twelve- and 18-month-olds point to provide information for others. Journal of Cognitive Development, 7, 173187.Google Scholar
Liu, J., Harris, A., and Kanwisher, N. (2002). Stages of processing in face perception: an MEG study. Nature Neuroscience, 5, 910916.Google Scholar
Logue, S., Chein, J., Gould, T., Holliday, E., and Steinberg, L. (2014). Adolescent mice, unlike adults, consume more alcohol in the presence of peers than alone. Developmental Science, 17, 7985.Google Scholar
Lohmann, H., and Tomasello, M. (2003). The role of language in the development of false belief understanding: a training study. Child Development, 74, 11301144.Google Scholar
Lombardo, M., Chakrabarti, B., Bullmore, E., Sadek, S., Pasco, G., Wheelwright, S., and Baron-Cohen, S. (2010). Atypical neural representation in autism. Brain, 133, 611624.CrossRefGoogle ScholarPubMed
Lufi, D., Tzischinsky, O., and Hadar, S. (2011). Delaying school starting time by one hour: some effects on attention levels in adolescents. Journal of Clinical Sleep Medicine, 7, 137143.CrossRefGoogle ScholarPubMed
Luna, B., Garver, K., Urban, T., Lazar, N., and Sweeney, J. (2004). Maturation of cognitive processes from late childhood to adulthood. Child Development, 75, 13571372.CrossRefGoogle ScholarPubMed
Luna, B., Marek, S., Larsen, B., Terro-Clemens, B., and Chahal, R. (2015). An integrative model of the maturation of cognitive control. Annual Reviews in Neuroscience, 38, 151170.Google Scholar
Luna, B., Padmanabhan, A., and O'Hearn, K. (2010). What has fMRI told us about the development of cognitive control through adolescence? Brain and Cognition, 72, 101113.Google Scholar
Luna, B., Thulborn, K.R., Munoz, D.P., Merriam, E.P., Garver, K.E., Minshew, N.J., and Sweeney, J.A. (2001). Maturation of widely distributed brain function subserves cognitive development. Neuroimage, 13, 786793.CrossRefGoogle ScholarPubMed
Lupien, S., McEwen, B. S., Gunnar, M., and Heim, C. (2009). Effects of stress throughout the lifespan on the brain, behavior and cognition. Nature Reviews Neuroscience, 10, 434445.Google Scholar
Magarinos, A., McEwen, B., Flugge, G., and Fuchs, E. (1996). Chronic psychosocial stress causes apical dendritic atrophy of hippocampal CA3 pyramidal neurons in subordinate tree shrews. Journal of Neuroscience, 16, 35343540.CrossRefGoogle ScholarPubMed
Maguire, E., Gadian, D., Johnsrude, I., Good, C., Ashburner, J., Frackowiak, R., and Frith, C. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences USA, 97, 43984403.Google Scholar
Mahy, C., Moses, L., and Pfeifer, J. (2014). How and where: theory-of-mind in the brain. Developmental Cognitive Neuroscience, 9, 6881.CrossRefGoogle ScholarPubMed
Manjunath, N., and Telles, S. (2001). Improved performance in the Tower of London test following yoga. Indian Journal of Physiological Pharmacology, 45, 351354.Google Scholar
Mannuzza, S., Klein, R., Bonagura, N., Malloy, P., Giampino, T., and Addalli, K. (1991). Hyperactive boys almost grown up: replication of psychiatric status. Archives of General Psychiatry, 10, 48774883.Google Scholar
Mantzoros, C., Flier, J., and Rogol, A. (1997). A longitudinal assessment of hormonal and physical alterations during normal puberty in boys. V. Rising leptin levels may signal the onset of puberty. Journal of Clinical Endocrinology and Metabolism, 82, 10661070.Google Scholar
Marsh, R., Zhu, H., Schultz, R., Quackenbush, G., Royal, J., Skudlarski, P., and Peterson, B. (2006). A developmental fMRI study of self-regulatory control. Human Brain Mapping, 27, 848863.Google Scholar
Marshall, W.A., and Tanner, J.M. (1969). Variations in pattern of pubertal changes in girls. Archives of Disease in Childhood, 44, 291303.Google Scholar
Marshall, W.A., and Tanner, J.M. (1970). Variations in pattern of pubertal changes in boys. Archives of Disease in Childhood, 45, 1323.CrossRefGoogle ScholarPubMed
Martiniuk, A., Senserrick, T., Lo, S., Williamson, A., Du, W., Grunstein, R., Woodward, M., Glozier, N., Stevenson, M., Norton, R., and Ivers, R. (2013). Sleep-deprived young drivers and the risk for crash: the DRIVE Prospective Cohort Study. JAMA Pediatrics, 167, 647655.CrossRefGoogle ScholarPubMed
Martos-Moreno, G., Chowen, J., and Argente, J. (2010). Metabolic signals in human puberty: effects of over and undernutrition. Molecular Cell Endocrinology, 324, 7081.CrossRefGoogle ScholarPubMed
Masten, C.L., Eisenberger, N.I., Pfeifer, J.H., and Dapretto, M. (2010). Witnessing peer rejection during early adolescence: neural correlates of empathy for experiences of social exclusion. Social Neuroscience, 5, 112.CrossRefGoogle ScholarPubMed
Matsumoto, M., and Hikosaka, O. (2009). Representation of negative motivational value in the primate lateral habenula. Nature Neuroscience, 12, 7784.Google Scholar
May, A., Hajak, G., Ganssbauer, S., Steffens, T., Langguth, B., Kleinjung, T., and Eichhammer, P. (2007). Structural brain alterations following 5 days of intervention: dynamic aspects of neuroplasticity. Cerebral Cortex, 17, 205210.CrossRefGoogle ScholarPubMed
McCandliss, B., and Noble, K. (2003). The development of reading impairment: a cognitive neuroscience model. Mental Retardation and Developmental Disabilities Research Review, 9, 196204.Google Scholar
McCartt, A., Mayhew, D., Braitman, K., Ferguson, S., and Simpson, H. (2009). Effects of age and experience on young driver crashes: review of recent literature. Traffic and Injury Prevention, 10, 209219.Google Scholar
McCartt, A., Teoh, E., Fields, M., Braitman, K., and Hellinga, L. (2010). Graduated licensing laws and fatal crashes of teenage drivers: a national study. Traffic and Injury Prevention, 11, 240248.CrossRefGoogle ScholarPubMed
McCutcheon, J., and Marinelli, M. (2009). Technical spotlight: age matters. European Journal of Neuroscience, 29, 9971014.Google Scholar
McLoyd, V. (1998). Socioeconomic disadvantage and child development. American Psychologist, 53, 185204.Google Scholar
McKnight, A., and McKnight, A. (2003). Young novice drivers: careless or clueless? Accident Analysis and Prevention, 35, 921925.Google Scholar
Mead, M. (1928). Coming of age in Samoa: a psychological study of primitive youth for western civilization. New York: William Morrow.Google Scholar
Mendle, J., Harden, K., Brooks-Gunn, J., and Graber, J. (2010). Development's tortoise and hare: pubertal timing, pubertal tempo, and depressive symptoms in boys and girls. Developmental Psychology, 46, 13411353.CrossRefGoogle ScholarPubMed
Mendle, J., Leve, L., Van Ryzin, M., Natsuaki, M., and Ge, X. (2011). Associations between early life stress, child maltreatment, and pubertal development among girls in foster care. Journal of Research on Adolescence, 21, 871880.Google Scholar
Menzel, R., and Giurfa, M. (2001). Cognitive architecture of a mini-brain: the honeybee. Trends in Cognitive Science, 5, 6271.Google Scholar
Meshi, D., Morawetz, C., and Heekeren, H. (2013). Nucleus accumbens response to gains in reputation for the self relative to gains for others predicts social media use. Frontiers in Human Neuroscience, 29, 439445.Google Scholar
Miller, E.K., and Cohen, J.D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167202.CrossRefGoogle ScholarPubMed
Miller, E.K., and Desimone, R. (1994). Parallel neuronal mechanisms for short-term memory. Science, 263, 520522.Google Scholar
Mills, K., Lalonde, F., Clasen, L., Giedd, J., and Blakemore, S. (2014). Developmental changes in the structure of the social brain in late childhood and adolescence. Social Cognitive Affective Neuroscience, 9, 123131.CrossRefGoogle ScholarPubMed
Milner, B. (1963). Effects of different brain lesions on card sorting. Archives of Neurology, 9, 9097.Google Scholar
Mitchell, J.P., Macrae, C., and Banaji, M. (2006). Dissociable medial prefrontal contributions to judgments of similar and dissimilar others. Neuron, 50, 655663.CrossRefGoogle ScholarPubMed
Mohammed, A., Jonsson, G., and Archer, T. (1986). Selective lesioning of forebrain noradrenaline neurons at birth abolishes the improved maze learning performance induced by rearing in complex environment. Brain Research, 398, 610.CrossRefGoogle ScholarPubMed
Monk, C., Weng, S., Wiggins, J., Kurapati, N., Louro, H., Carrasco, M., and Lord, C. (2010). Neural circuitry of emotional face processing in autism spectrum disorder. Journal of Psychiatry and Neuroscience, 35, 105114.CrossRefGoogle Scholar
Monteleone, P., Luisi, M., Colurcio, B., Casarosa, E., Monteleone, P., Ioime, R., and Maj, M. (2001). Plasma levels of neuroactive steroids are increased in untreated women with anorexia nervosa or bulimia nervosa. Psychosomatic Medicine, 63, 6268.Google Scholar
Moore, C. (2009). Fairness in children's resource allocation depends on the recipient. Psychological Science, 20, 944948.Google Scholar
Morris, D., Jones, M., Schoemaker, M., Ashworth, A., and Swerdlow, A. (2011). Familial concordance for age at menarche: analyses from the Breakthrough Generations Study. Paediatric Perinatal Epidemiology, 25, 306311.Google Scholar
Morris, J., Frith, C., Perrett, D., Rowland, D., Young, A., Calder, A., and Dolan, R. (1996). A differential neural response in the human amygdala to fearful and happy facial expressions. Nature, 383, 812815.Google Scholar
Mosconi, M., Mack, P., McCarthy, G., and Pelphrey, K. (2005). Taking an “intentional stance” on eye-gaze shifts: a functional neuroimaging study of social perception in children. Neuroimage, 27, 247252.CrossRefGoogle ScholarPubMed
Munakata, Y., and Pfaffly, J. (2004). Hebbian learning and development. Developmental Science, 7, 141148.Google Scholar
Myers, C.A., Vandermusten, M., Farris, E.A., Hancock, R., Gimenez, P., Black, ,…Hoeft, F. (2014). White matter morphometric changes uniquely predict children's reading acquisition. Psychological Science, 25, 18701883.Google Scholar
Nagy, Z., Westerberg, H., and Klingberg, T. (2004). Maturation of white matter is associated with the development of cognitive functions during childhood. Journal of Cognitive Neuroscience, 16, 12271233.CrossRefGoogle ScholarPubMed
Nakao, H., and Itakura, S. (2009). An integrated view of empathy: psychology, philosophy, and neuroscience. Integrative Psychology and Behavioral Science, 43, 4252.Google Scholar
National Sleep Foundation (2011). Sleep in America poll: teens and sleep.Washington, DC: National Sleep Foundation.Google Scholar
Navarro, V., Fernandez-Fernandez, R., Castellano, J., Roa, J., Mayen, A., Barreiro, M., and Tena-Sempere, M. (2004). Advanced vaginal opening and precocious activation of the reproductive axis by KiSS-1 peptide, the endogenous ligand of GPR54. Journal of Physiology, 561, 379386.Google Scholar
Needham, A., Barrett, T., and Peterman, K. (2002). A pick-me-up for infants’ exploratory skills: early stimulated experiences reaching for objects using “sticky mittens” enhances young infants’ object exploration skills. Infant Behavior and Development, 25, 279295.CrossRefGoogle Scholar
Negriff, S., Susman, E., and Trickett, P. (2011). The developmental pathway from pubertal timing to delinquency and sexual activity from early to late adolescence. Journal of Youth and Adolescence, 40, 13431356.Google Scholar
Nelson, E., Herman, K., Barrett, C., Noble, P., Wojteczko, K., Chisholm, K., Delaney, D., Ernst, M., Fox, N.A., Suomi, S.J., Winslow, J.T., and Pine, D.S. (2009). Adverse rearing experiences enhance responding to both aversive and rewarding stimuli in juvenile rhesus monkeys. Biological Psychiatry, 66, 702704.CrossRefGoogle ScholarPubMed
Nelson, E., Lieibenluft, E., McClure, E., and Pine, D.S. (2005). The social re-orientation of adolescence: a neuroscience perspective on the process and its relation to psychopathology. Psychological Medicine, 35, 163174.Google Scholar
Nemmi, F., Helander, E., Helenius, O., Almeida, R., Hassler, M., Räsänen, P., and Klingberg, T. (2016). Behavior and neuroimaging at baseline predict individual response to combined mathematical and working memory training in children. Developmental Cognitive Neuroscience, 20, 4351.Google Scholar
Nguyen, T., McCracken, J., Ducharme, S., Botteron, K., Mahabir, M., Johnson, W., Israel, M., Evans, A.C., Karama, S., and Brain Development Cooperative (2013). Testosterone-related cortical maturation across childhood and adolescence. Cerebral Cortex, 23, 14241432.CrossRefGoogle ScholarPubMed
Nichols, T., Das, S., Eickhoff, S., Evans, A., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M.P., Podrack, R.A., Poline, J.-B., Proal, E., Thirion, B., Van Essen, D.C., White, T., and Yeo, B. (2015). Best practices in data analysis and sharing in neuroimaging using MRI. bioRxiv.Google Scholar
Nieuwenhuys, R., Donkelaar, H., and Nicholson, H. (1998). The central nervous system of vertebrates, vol. 3. Berlin: Springer.Google Scholar
Nishimura, H., Hashikawa, K., Doi, K., Iwaki, T., Watanabe, Y., Kusuoka, H., Nishimura, T., and Kubo, T. (1999). Sign language “heard” in the auditory cortex. Nature, 397, 116.CrossRefGoogle ScholarPubMed
Noble, K., Houston, S., Brito, N., Bartsch, H., Kan, E., Kuperman, J., … Sowell, E. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18, 773778.CrossRefGoogle ScholarPubMed
Noble, K., McCandliss, B., and Farah, M. (2007). Socioeconomic gradients predict individual differences in neurocognitive abilities. Developmental Science, 10, 464480.Google Scholar
Nomi, J.S., and Uddin, L.Q. (2015). Face processing in autism spectrum disorders: from brain regions to brain networks. Neuropsychology, 71, 201216.Google Scholar
Norman, K., Polyn, S., Detre, G., and Haxby, J. (2006). Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10, 424430.Google Scholar
Nottelmann, E., Susman, E.J., Dorn, L., Inoff-Germain, G., Loriaux, D., Cutler, G., and Chrousos, G. (1987). Developmental processes in early adolescence. Relations among chronologic age, pubertal stage, height, weight, and serum levels of gonadotropins, sex steroids, and adrenal androgens. Journal of Adolescent Health Care, 8, 246260.Google Scholar
Oberman, L., Hubbard, E., McCleery, J., Altschuler, E., Ramachandran, V., and Pineda, J. (2005). EEG evidence for mirror neuron dysfunction in autism spectrum disorders. Cognition Brain Research, 24, 190198.CrossRefGoogle ScholarPubMed
Oberman, L., and Pascual-Leone, A. (2013). Changes in plasticity across the lifespan: cause of disease and target for intervention. Progress in Brain Research, 207, 91120.Google Scholar
Olds, J., and Milner, P. (1954). Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. Journal of Comparative Physiology and Psychology, 47, 419427.CrossRefGoogle ScholarPubMed
Oleson, P., Macoveanu, J., Tegner, J., and Klingberg, T. (2007). Brain activity related to working memory and distraction in children and adults. Cerebral Cortex, 17, 10471054.CrossRefGoogle Scholar
Olesen, P., Westerberg, H., and Klingberg, T. (2004). Increased prefrontal and parietal activity after training of working memory. Nature Neuroscience, 7, 7579.Google Scholar
Onoda, K., Okamoto, Y., Nakashima, K., Nittono, H., Yoshimura, S., Yamawaki, S., and Ura, M. (2010). Does low self-esteem enhance social pain? The relationship between trait self-esteem and anterior cingulate cortex activation induced by ostracism. Social Cognitive and Affective Neuroscience, 5, 385391.Google Scholar
Op de Macks, Z., Gunther Moor, B., Overgaauw, S., Guroglu, B., Dahl, R., and Crone, E. (2011). Testosterone levels correspond with increased ventral striatum activation in response to monetary rewards in adolescents. Developmental Cognitive Neuroscience, 1, 506516.Google Scholar
Osterlund, M., Keller, E., and Hurd, Y. (1999). The human forebrain has discrete estrogen receptor messenger RNA expression: high levels in the amygdaloid complex. Neuroscience, 95, 333342.Google Scholar
Ouimet, M., Simons-Morton, B., Zador, P., Lerner, N., Freedman, M., Duncan, G., and Wang, J. (2010). Using the U.S. National Household Travel Survey to estimate the impact of passenger characteristics on young drivers' relative risk of fatal crash involvement. Accident Analysis and Prevention, 42, 689694.CrossRefGoogle Scholar
Overgaauw, S., Guroglu, B., Rieffe, C., and Crone, E. (2014). Behavior and neural correlates of empathy in adolescents. Developmental Neuroscience, 36, 210219.Google Scholar
Owens, J.; Adolescent Sleep Working Group; Committee on Adolescence (2014). Insufficient sleep in adolescents and young adults: an update on causes and consequences. Pediatrics, 134, e921e932.Google Scholar
Owens, J., and Jones, C. (2011). Parental knowledge of healthy sleep in young children: results of a primary care clinic survey. Journal of Developmental and Behavioral Pediatrics, 32, 447453.Google Scholar
Padmanabhan, A., Geier, C., Ordaz, S., Teslovich, T., and Luna, B. (2011). Developmental changes in brain function underlying the influence of reward processing on inhibitory control. Developmental Cognitive Neuroscience, 1, 517529.CrossRefGoogle ScholarPubMed
Papagiannopoulou, E., Chitty, K., Hermens, D., Hickie, I., and Lagopoulos, J. (2014). A systematic review and meta-analysis of eye-tracking studies in children with autism spectrum disorders. Social Neuroscience, 9, 610632.Google ScholarPubMed
Pascalis, O., de Haan, M., and Nelson, C. (2002). Is face processing species-specific during the first year of life? Science, 296, 13211323.CrossRefGoogle ScholarPubMed
Passarotti, A., Paul, B., Bussiere, J., Buxton, R., Wong, E., and Stiles, J. (2003). The development of face and location processing: an fMRI study. Developmental Science, 6, 100117.Google Scholar
Passingham, R.E., Stephan, K.E., and Kotter, R. (2002). The anatomical basis of functional localization in the cortex. Nature Reviews Neuroscience, 3, 606616.Google Scholar
Paus, T. (2013). How environment and genes shape the adolescent brain. Hormones and Behavior, 64, 195202.Google Scholar
Paus, T., Keshavan, M., and Giedd, J. (2008). Why do many psychiatric disorders emerge during adolescence? Nature Reviews Neuroscience, 9, 947957.Google Scholar
Pears, K., and Moses, L. (2003). Demographics, parenting, and theory of mind in preschool children. Social Development, 12, 120.CrossRefGoogle Scholar
Peelen, M., Glaser, B., Vuilleumier, P., and Eliez, S. (2009). Differential development of selectivity for faces and bodies in the fusiform gyrus. Developmental Science, 12, F16F25.Google Scholar
Pelphrey, K., Morris, J., and McCarthy, G. (2005). Here's looking at you, kid: neural systems underlying face and gaze processing in fragile X syndrome. Archives of General Psychiatry, 61, 281288.Google Scholar
Pelphrey, K., Sasson, N., Reznick, J., Paul, G., Goldman, B., and Piven, J. (2002). Visual scanning of faces in autism. Journal of Autism and Developmental Disorders, 32, 249261.Google Scholar
Pelphrey, K.A., Shultz, S., Hudac, C.M., and Vander Wyk, B.C. (2011). Research review: constraining heterogeneity: the social brain and its development in autism spectrum disorder. Journal of Child Psychology and Psychiatry, 52, 631644.Google Scholar
Peper, J., Brouwer, R., Schnack, H., van Baal, G., van Leeuwen, M., van den Berg, S., and Hulshoff Pol, H. (2008). Cerebral white matter in early puberty is associated with luteinizing hormone concentrations. Psychoneuroendocrinology, 33, 909915.Google Scholar
Peper, J., and Dahl, R. (2013). The teenage brain surging hormones – brain-behavior interactions during puberty. Current Directions in Psychological Science, 22, 134139.CrossRefGoogle ScholarPubMed
Peper, J., Koolschijn, P., and Crone, E. (2013). Development of risk taking: contributions from adolescent testosterone and the orbitofrontal cortex. Journal of Cognitive Neuroscience, 25, 21412150.CrossRefGoogle Scholar
Peper, J., Schnack, H., Brouwer, R., Van Baal, G., Pjetri, E., Szekely, E., van Leeuwen, M., van den Berg, S.M., Collins, D.L., Evans, A.C., Boomsma, D.I., Kahn, R.S., and Hulshoff Pol, H. (2009). Heritability of regional and global brain structure at the onset of puberty: a magnetic resonance imaging study in 9-year-old twin pairs. Human Brain Mapping, 30, 21842196.Google Scholar
Perlman, S., and Pelphrey, K. (2011). Developing connections for affective regulation: age-related changes in emotional brain connectivity. Journal of Experimental Child Psychology, 108, 607620.CrossRefGoogle ScholarPubMed
Perrin, A. (2015). Social networking usage: 2005–2015. Pew Research Center.Google Scholar
Perrin, J., Leonard, G., Perron, M., Pike, G., Pitiot, A., Richer, L., Veillette, S., Pausova, Z., and Paus, T. (2009). Sex differences in the growth of white matter during adolescence. Neuroimage, 45, 10551066.CrossRefGoogle ScholarPubMed
Petersen, A.C., Crockett, L., Richards, M., and Boxer, A. (1988). A self-report measure of pubertal status: reliability, validity, and initial norms. Journal of Youth and Adolescence, 17, 117133.CrossRefGoogle ScholarPubMed
Pezawas, L., Meyer-Lindenberg, A., Drabant, E., Verchinski, B., Munoz, K., Kolachana, B., Egan, M.F., Mattay, V.S., Hariri, A.R., and Weinberger, D. (2005). 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nature Neuroscience, 8, 828834.Google Scholar
Pfeifer, J., and Allen, N. (2012). Arrested development? Reconsidering dual-systems models of brain function in adolescence and disorders. Trends in Cognitive Sciences, 16, 322329.CrossRefGoogle ScholarPubMed
Pfeifer, J., Iacoboni, M., Mazziotta, J., and Dapretto, M, (2008). Mirroring others’ emotions relates to empathy and social abilities during childhood. Neuroimage, 39, 20762085.Google Scholar
Pfeifer, J., Lieberman, M., and Dapretto, M. (2007). “I know you are but what am I?!”: neural bases of self- and social knowledge retrieval in children and adults. Journal of Cognitive Neuroscience, 19, 13231337.Google Scholar
Pfeifer, J., and Peake, S. (2012). Self-development: integrating cognitive, socioemotional, and neuroimaging perspectives. Developmental Cognitive Neuroscience, 2, 5569.Google Scholar
Pfeifer, J.H., Masten, C.L., Borofsky, L., Dapretto, M., Fuligni, A.S., and Lieberman, M. (2009). Neural correlates of direct and reflected self-appraisals in adolescents and adults: when social perspective-taking informs self-perception. Child Development, 80, 10161038.Google Scholar
Pfeifer, J., Masten, C., Moore, W.R., Oswald, T., Mazziotta, J., Iacoboni, M., and Dapretto, M. (2011). Entering adolescence: resistance to peer influence, risky behavior, and neural changes in emotion reactivity. Neuron, 69, 10291036.CrossRefGoogle ScholarPubMed
Pickrell, T. (2006). Driver alcohol involvement in fatal crashes by age group and vehicle type. Washington, DC: National Highway Traffic Safety Administration.Google Scholar
Pierce, K., Haist, F., Sedaghat, F., and Courchesne, E. (2004). The brain response to personally familiar faces in autism: findings of fusiform activity and beyond. Brain, 127, 27032716.Google Scholar
Pierpaoli, C., Jezzard, P., Basser, P., Barnett, A., and Di Chiro, G. (1996). Diffusion tensor MR imaging of the human brain. Radiology, 201, 637648.CrossRefGoogle ScholarPubMed
Pine, D., Lissek, S., Klein, R., Mannuzza, S., Moulton, J., 3rd, Guardino, M., and Woldehawariat, G. (2004). Face-memory and emotion: associations with major depression in children and adolescents. Journal of Child Psychology and Psychiatry, 45, 11991208.Google Scholar
Poldrack, R. (2015). Is “efficiency” a useful concept in cognitive neuroscience? Developmental Cognitive Neuroscience, 11, 1217.Google Scholar
Pollak, S.D., Nelson, C., Schlaak, M., Roeber, B., Wewerka, S., Wiik, K., Frenn, K.A., Loman, M.M., and Gunnar, M. (2010). Neurodevelopmental effects of early deprivation in postinstitutionalized children. Child Development, 81, 224236.CrossRefGoogle ScholarPubMed
Post, G., and Kemper, H. (1993). Nutritional intake and biological maturation during adolescence. The Amsterdam growth and health longitudinal study. European Journal of Clinical Nutrition, 47, 400408.Google Scholar
Power, J., Barnes, K., Snyder, A., Schlaggar, B., and Petersen, S. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59, 21422154.Google Scholar
Preuss, T.M. (2000). What's human about the human brain? In Gazzaniga, M. (ed.), The new cognitive neurosciences (2nd edn.). Cambridge, MA: MIT Press.Google Scholar
Puce, A., Allison, T., Bentin, S., Gore, J., and McCarthy, G. (1998). Temporal cortex activation in humans viewing eye and mouth movements. Journal of Neuroscience, 18, 21882199.Google Scholar
Qu, Y., Galván, A., Fuligni, A., Lieberman, M., and Telzer, E. (2015). Longitudinal changes in prefrontal cortex activation underlie declines in adolescent risk taking. Journal of Neuroscience, 35, 11,30811,314.Google Scholar
Radley, J., Rocher, A., Janssen, W., Hof, P., McEwen, B., and Morrison, J. (2005). Reversibility of apical dendritic retraction in the rat medial prefrontal cortex following repeated stress. Experimental Neurology, 196, 199203.CrossRefGoogle ScholarPubMed
Raichle, M., and Snyder, A. (2007). A default mode of brain function: a brief history of an evolving idea. Neuroimage, 37, 10831090; discussion 10971099.Google Scholar
Ramón y Cajal, S. (1899). Textura del sistema nervioso del hombre y de los vertebrados. Madrid: Imprenta y Librería de Nicolás Moya.Google Scholar
Rao, U., Sidhartha, T., Harker, K., Bidesi, A., Chen, L., and Ernst, M. (2011). Relationship between adolescent risk preferences on a laboratory task and behavioral measures of risk-taking. Journal of Adolescent Health, 48, 151158.Google Scholar
Raschle, N., Lee, M., Buechler, R., Christodoulou, J., Chang, M., Vakil, M., and Gaab, N. (2009). Making MR imaging child's play – pediatric neuroimaging protocol, guidelines and procedure. Journal of Visualized Experiments, 29, 1309.Google Scholar
Rauschecker, J. (1995). Compensatory plasticity and sensory substitution in the cerebral cortex. Trends in Neuroscience, 18, 3643.Google Scholar
Raznahan, A., Shaw, P., Lerch, J., Clasen, L., Greenstein, D., Berman, R., … Giedd, J.N. (2014). Longitudinal four-dimensional mapping of subcortical anatomy in human development. Proceedings of the National Academy of Sciences USA, 111, 15921597.Google Scholar
Reyna, V., and Farley, F. (2006). Risk and rationality in adolescent decision making: implications for theory, practice, and public policy. Psychological Science in the Public Interest, 7, 144.Google Scholar
Rivers, S., Reyna, V., and Mills, B. (2008). Risk taking under the influence: a fuzzy-trace theory of emotion in adolescence. Developmental Review, 28, 107144.CrossRefGoogle ScholarPubMed
Roa, J., Garcia-Galiano, D., Castellano, J., Gaytan, F., Pinilla, L., and Tena-Sempere, M. (2010). Metabolic control of puberty onset: new players, new mechanisms. Molecular Cell Endocrinology, 324, 8794.Google Scholar
Robinson, D., Heien, M., and Wightman, R. (2002). Frequency of dopamine concentration transients increases in dorsal and ventral striatum of male rats during introduction of conspecifics. Journal of Neuroscience, 22, 10,47710,486.Google Scholar
Robinson, D., Zitzman, D., Smith, K., and Spear, L. (2011). Fast dopamine release events in the nucleus accumbens of early adolescent rats. Neuroscience, 176, 296307.Google Scholar
Rogers, S., and Pennington, B. (1991). A theoretical approach to the deficits in infantile autism. Developmental Psychology, 3, 137162.Google Scholar
Roitman, M., Wheeler, R., Wightman, R., and Carelli, R. (2008). Real-time chemical responses in the nucleus accumbens differentiate rewarding and aversive stimuli. Nature Neuroscience, 11, 13761377.Google Scholar
Romer, D., Lee, Y., McDonald, C., and Winston, F. (2014). Adolescence, attention allocation, and driving safety. Journal of Adolescent Health, 54, S6S15.Google Scholar
Rosenfield, R., Lipton, R., and Drum, M. (2009). Thelarche, pubarche, and menarche attainment in children with normal and elevated body mass index. Pediatrics, 123, 8488.Google Scholar
Rosenzweig, M., Krech, D., Bennett, E., and Diamond, M. (1962). Effects of environmental complexity and training on brain chemistry and anatomy: a replication and extension. Journal of Comparative Physiology and Psychology, 55, 429437.Google Scholar
Rothmayr, C., Sodian, B., Hajak, G., Dohnel, K., Meinhardt, J., and Sommer, M. (2010). Common and distinct neural networks for false-belief reasoning and inhibitory control. Neuroimage, 56, 17051713.CrossRefGoogle ScholarPubMed
Routtenberg, A. (1978). The reward system of the brain. Scientific American, 7, 154164.CrossRefGoogle Scholar
Rovee-Collier, C., and Hayne, H. (2000). Memory in infancy and early childhood. In Tulving, E. and Craik, F. (eds.), The Oxford handbook of memory (pp. 267282). Oxford: Oxford University Press.CrossRefGoogle Scholar
Rubia, K., Overmeyer, S., Taylor, E., Brammer, S., Williams, S.C., Simmons, A., et al. (2000). Functional frontalisation with age: mapping neurodevelopmental trajectories with fMRI. Neuroscience and Biobehavioral Reviews, 24, 1319.Google Scholar
Rubia, K., Smith, A., Taylor, E., and Brammer, M. (2007). Linear age-correlated functional development of inferior fronto-striato-cerebellar networks during response inhibition and anterior cingulate during error-related processes. Human Brain Mapping, 28, 11631177.Google Scholar
Rubia, K., Smith, A., Woolley, J., Nosarti, C., Heyman, I., Taylor, E., and Brammer, M. (2006). Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Human Brain Mapping, 27, 973993.Google Scholar
Sabbagh, M., Bowman, L., Evraire, L., and Ito, J. (2009). Neurodevelopmental correlates of theory of mind in preschool children. Child Development, 80, 11471162.Google Scholar
Salas, R., Baldwin, P., de Biasi, M., and Montague, P.R. (2010). BOLD responses to negative reward prediction errors in human habenula. Frontiers in Human Neuroscience, 11, 3645.Google Scholar
Sallet, J., Mars, R., Noonan, M., Andersson, J., O'Reilly, J., Jbabdi, S., Croxson, P.L., Jenkinson, M., Miller, K.L., and Rushworth, M. (2011). Social network size affects neural circuits in macaques. Science, 334, 697700.Google Scholar
Sanchez-Garrido, M., and Tena-Sempere, M. (2013). Metabolic control of puberty: roles of leptin and kisspeptins. Hormones and Behavior, 64, 187194.CrossRefGoogle ScholarPubMed
Sanfey, A.G., Rilling, J.K., Aronson, J., Nystrom, L.E., and Cohen, J.D. (2003). The neural basis of economic decision-making in the Ultimatum Game. Science, 300, 17551758.Google Scholar
Sato, S., Schulz, K., Sisk, C., and Wood, R. (2008). Adolescents and androgens, receptors and rewards. Hormones and Behavior, 53, 647658.CrossRefGoogle ScholarPubMed
Satterthwaite, T., Elliott, M., Gerraty, R., Ruparel, K., Loughead, J., Calkins, M., Eickhoff, S.B., Hakonarson, H., Gur, R.C., Gur, R.E., and Wolf, D. (2013). An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage, 64, 240256.Google Scholar
Satterthwaite, T., Wolf, D., Loughead, J., Ruparel, K., Elliott, M., Hakonarson, H., Gur, R.C., and Gur, R. (2012). Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage, 60, 623632.Google Scholar
Saxe, R., and Kanwisher, N. (2003). People thinking about thinking people. The role of the temporo-parietal junction in “theory of mind.” Neuroimage, 19, 18351842.Google Scholar
Schendan, H., Ganis, G., and Kutas, M. (1998). Neurophysiological evidence for visual perceptual categorization of words and faces within 150 ms. Psychophysiology, 35, 240251.Google Scholar
Scherf, K.S., Behrmann, M., and Dahl, R.E. (2012). Facing changes and changing faces in adolescence: a new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development. Developmental Cognitive Neuroscience, 2, 199219.Google Scholar
Scherf, K. S., Behrmann, M., Humphreys, K., and Luna, B. (2007). Visual category-selectivity for faces, places and objects emerges along different developmental trajectories. Developmental Science, 10, F15F30.Google Scholar
Scherf, K.S., Luna, B., Avidan, G., and Behrmann, M. (2011). “What” precedes “which”: developmental neural tuning in face- and place-related cortex. Cerebral Cortex, 21, 19631980.Google Scholar
Scherf, K., Smyth, J., and Delgado, M. (2013). The amygdala: an agent of change in adolescent neural networks. Hormones and Behavior, 64(2), 298313.Google Scholar
Schlaggar, B., Brown, T., Lugar, H., Visscher, K., Miezin, F., and Petersen, S. (2002). Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science, 296, 14761479.Google Scholar
Schlaug, G., Forgeard, M., Zhu, L., Norton, A., Norton, A., and Winner, E. (2009). Training-induced neuroplasticity in young children. Annals of the New York Academy of Sciences, 1169, 205208.Google Scholar
Schlegel, A. (2001). The global spread of adolescent culture. In Crocket, L. and Silbereisen, R. (eds.), Negotiating adolescence in times of social change (pp. 6386). Cambridge: Cambridge University Press.Google Scholar
Schlund, M.W., Cataldo, M.F., Siegle, G.J., Ladouceur, C.D., Silk, J.S., Forbes, E.E., and Ryan, N.D. (2011). Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance. Behavior Brain Function, 7, 10.Google Scholar
Schultz, W., Dayan, P., and Montague, P.R. (1997). A neural substrate of prediction and reward. Science, 275, 15931599.CrossRefGoogle ScholarPubMed
Schultz, J., Imamizu, H., Kawato, M., and Frith, C. (2004). Activation of the human superior temporal gyrus during observation of goal attribution by intentional objects. Journal of Cognitive Neuroscience, 16, 16951705.Google Scholar
Schultz, R., Gauthier, I., Klin, A., Fulbright, R., Anderson, A., Volkmar, F., and Gore, J. (2000). Abnormal ventral temporal cortical activity during face discrimination among individuals with autism and Asperger syndrome. Archives of General Psychiatry, 57, 331340.CrossRefGoogle ScholarPubMed
Schweren, L., de Zeeuw, P., and Durston, S. (2013). MR imaging of the effects of methylphenidate on brain structure and function in attention-deficit/hyperactivity disorder. European Journal of Neuropsychopharmacology, 23, 11511164.CrossRefGoogle ScholarPubMed
Scott, E. (2000). The legal construction of adolescence. Hofstra Law Review, 29, 547598.Google Scholar
Scott, E., and Steinberg, L. (2008). Rethinking juvenile justice. Cambridge, MA: Harvard University Press.Google Scholar
Seitz, V., Rosenbaum, L., and Apfel, N. (1985). Effects of family support intervention: a ten-year follow-up. Child Development, 56(2), 376391.CrossRefGoogle ScholarPubMed
Senju, A., Yaguchi, K., Tojo, Y., and Hasegawa, T. (2003). Eye contact does not facilitate detection in children with autism. Cognition, 89, B43B51.Google Scholar
Shackman, A., Salomons, T., Slagter, H., Fox, A., Winter, J., and Davidson, R. (2011). The integration of negative affect, pain, and cognitive control in the cingulate cortex. Nature Reviews Neuroscience, 12, 154167.CrossRefGoogle ScholarPubMed
Shaw, P., Gogtay, N., and Rapoport, J. (2010). Childhood psychiatric disorders as anomalies in neurodevelopmental trajectories. Human Brain Mapping, 31, 917925.CrossRefGoogle ScholarPubMed
Shaw, P., Sharp, W., Morrison, M., Eckstrand, K., Greenstein, D., Clasen, L., and Rapoport, J. (2009). Psychostimulant treatment and the developing cortex in attention deficit hyperactivity disorder. American Journal of Psychiatry, 166, 5863.Google Scholar
Shedler, J., and Block, J. (1990). Adolescent drug use and psychological health. A longitudinal inquiry. American Psychologist, 45, 612630.CrossRefGoogle ScholarPubMed
Shepherd, G. (1998). The synaptic organization of the brain. Oxford: Oxford University Press.Google Scholar
Sherman, L., Payton, A., Hernandez, L., Greenfield, P., and Dapretto, M. (2016). The power of the like in adolescence: effects of peer influence on neural and behavioral responses to social media. Psychological Science, 27, 10271035.Google Scholar
Sibson, N., Dhankhar, A., Mason, G., Rothman, D., Behar, K., and Shulman, R. (1998). Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity. Proceedings of the National Academy of Sciences USA, 95, 316321.Google Scholar
Siebner, H., and Rothwell, J. (2003). Transcranial magnetic stimulation: new insights into representational cortical plasticity. Experimental Brain Research, 148, 116.Google Scholar
Simos, P., Fletcher, J., Bergman, E., Breier, J., Foorman, B., Castillo, E., Davis, R., Fitzgerald, M., and Papanicolaou, A. (2002). Dyslexia-specific brain activation profile becomes normal following successful remedial training. Neurology, 58, 12031213.Google Scholar
Sisk, C., and Foster, D. (2004). The neural basis of puberty and adolescence. Nature Neuroscience, 7, 10401047.CrossRefGoogle ScholarPubMed
Sisk, C., and Zehr, J. (2005). Pubertal hormones organize the adolescent brain and behavior. Frontiers in Neuroendocrinology, 26, 163174.CrossRefGoogle ScholarPubMed
Slee, P., Campbell, M., and Spears, B. (2012). Child, adolescent and family development (3rd edn.). Cambridge: Cambridge University Press.Google Scholar
Slovic, P., Finucane, M., Peters, E., and MacGregor, D. (2004). Risk as analysis and risk as feelings: some thoughts about affect, reason, risk and rationality. Risk Analysis, 24, 311322.CrossRefGoogle ScholarPubMed
Smeltzer, M., Curtis, J., Aragona, B., and Wang, Z. (2006). Dopamine, oxytocin, and vasopressin receptor binding in the medial prefrontal cortex of monogamous and promiscuous voles. Neuroscience Letters, 394, 146151.Google Scholar
Smith, D., Xiao, L., and Bechara, A. (2012). Decision making in children and adolescents: impaired Iowa Gambling Task performance in early adolescence. Developmental Psychology, 48, 11801187.Google Scholar
Smith, I., and Beasley, M. (1989). Intelligence and behavior in children with early treated phenylketonuria. European Journal of Clinical Nutrition, 43, 15.Google Scholar
Smith, L., and Thelen, E. (2003). Development as a dynamic system. Trends in Cognitive Sciences, 7, 343348.CrossRefGoogle ScholarPubMed
Smith, L., Thelen, E., Titzer, R., and McLin, D. (1999). Knowing in the context of acting: the task dynamics of the A-not-B error. Psychological Review, 106, 235260.Google Scholar
Snow, C., and Hoefnagel-Hohle, M. (1977). Age differences in the pronunciation of foreign sounds. Language and Speech, 20, 357365.CrossRefGoogle ScholarPubMed
Sokoloff, L. (1973). Metabolism of ketone bodies by the brain. Annual Reviews of Medicine, 24, 271280.Google Scholar
Somerville, L.H. (2013). The teenage brain: sensitivity to social evaluation. Current Directions in Psychological Science, 22, 121127.Google Scholar
Somerville, L., and Casey, B. (2010). Developmental neurobiology of cognitive control and motivational systems. Current Opinion in Neurobiology, 20, 236241.CrossRefGoogle ScholarPubMed
Somerville, L., Hare, T., and Casey, B.J. (2011). Frontostriatal maturation predicts cognitive control failure to appetitive cues in adolescents. Journal of Cognitive Neuroscience, 23, 21232134.Google Scholar
Somerville, L., Heatherton, T., and Kelley, A. (2006). Anterior cingulate cortex responds differentially to expectancy violation and social rejection. Nature Neuroscience, 9, 10071008.Google Scholar
Somerville, L., Jones, R., Ruberry, E., Dyke, J., Glover, G., and Casey, B.J. (2013). The medial prefrontal cortex and the emergence of self-conscious emotion. Psychological Science, 24, 15541562.CrossRefGoogle ScholarPubMed
Sowell, E., Peterson, B., Thompson, P., Welcome, S., Henkenius, A., and Toga, A. (2003). Mapping cortical change across the human life span. Nature Neuroscience, 6, 309315.Google Scholar
Sowell, E., Thompson, P., Holmes, C., Jernigan, T., and Toga, A. (1999). In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nature Neuroscience, 2, 859861.Google Scholar
Spear, L. (2000). The adolescent brain and age-related behavioral manifestations. Neuroscience and Biobehavioral Reviews, 24, 417463.CrossRefGoogle ScholarPubMed
Spear, L. (2011). Rewards, aversions and affect in adolescence: emerging convergences across laboratory animal and human data. Developmental Cognitive Neuroscience, 1, 392400.Google Scholar
Spear, L.P. (2013). Adolescent neurodevelopment. Journal of Adolescent Health, 52, S7S13.CrossRefGoogle ScholarPubMed
Spencer, N., Bambang, S., Logan, S., and Gill, L. (1999). Socioeconomic status and birth weight: comparison of an area-based measure with the Registrar General's social class. Journal of Epidemiology and Community Health, 53, 495498.Google Scholar
Spencer-Smith, M., and Klingberg, T. (2015). Benefits of a working memory training program for inattention in daily life: a systematic review and meta-analysis. PLoS One, 10, e0119522.CrossRefGoogle ScholarPubMed
Spielberg, J., Jarcho, J., Dahl, R., Pine, D., Ernst, M., and Nelson, E. (2015). Anticipation of peer evaluation in anxious adolescents: divergence in neural activation and maturation. Social Cognitive and Affective Neuroscience, 10, 10841091.Google Scholar
Spielberg, J., Olino, T., Forbes, E., and Dahl, R. (2014). Exciting fear in adolescence: does pubertal development alter threat processing? Developmental Cognitive Neuroscience, 8, 8695.Google Scholar
Stang, J., and Story, M. (2005). Guidelines for adolescent nutrition services. Center for Applied Research and Educational Improvement. St. Paul: University of Minnesota.Google Scholar
Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78106.Google Scholar
Steinberg, L. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52, 216224.Google Scholar
Steinberg, L. (2014). Age of opportunity: lessons from the new science of adolescence. New York: Mariner Books.Google Scholar
Steinberg, L., Albert, D., Cauffman, E., Banich, M., Graham, S., and Woolard, J. (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: evidence for a dual systems model. Developmental Psychology, 44, 17641768.Google Scholar
Steinberg, L., Cauffman, E., Woolard, J., Graham, S., and Banich, M. (2009). Are adolescents less mature than adults? Minors' access to abortion, the juvenile death penalty and the alleged APA “Flip-Flop.” American Psychologist, 64, 583594.Google Scholar
Steinberg, L., Graham, S., O'Brien, L., Woolard, J., Cauffman, E., and Banich, M. (2009). Age differences in future orientation and delay discounting. Child Development, 80, 2844.CrossRefGoogle ScholarPubMed
Steinberg, L., and Morris, A. (2001). Adolescent development. Annual Review of Psychology, 52, 83110.Google Scholar
Stevens, M., Kiehl, K., Pearlson, G., and Calhoun, V. (2007). Functional neural networks underlying response inhibition in adolescents and adults. Behavioural Brain Research, 181, 1222.Google Scholar
Sturman, D., and Moghaddam, B. (2012). Striatum processes reward differently in adolescents versus adults. Proceedings of the National Academy of Sciences USA, 109, 17191724.Google Scholar
Sussman, S. (2002). Effects of sixty-six adolescent tobacco use cessation trials and seventeen prospective studies of self initiated quitting. Tobacco Induced Diseases, 1, 3581.CrossRefGoogle ScholarPubMed
Swartz, J., Carrasco, M., Wiggins, J., Thomason, M., and Monk, C. (2014). Age-related changes in the structure and function of prefrontal cortex–amygdala circuitry in children and adolescents: a multi-modal imaging approach. Neuroimage, 86, 212220.CrossRefGoogle ScholarPubMed
Swartz, J.R., Phan, K.L., Angstadt, M., Klumpp, H., Fitzgerald, K.D., and Monk, C.S. (2014). Altered activation of the rostral anterior cingulate cortex in the context of emotional face distractors in children and adolescents with anxiety disorders. Depression and Anxiety, 31, 870879.Google Scholar
Sweeney, J., Mintun, M., Kwee, S., Wiseman, M., Brown, D., Rosenberg, D.R., and Carl, J. (1996). Positron emission tomography study of voluntary saccadic eye movements and spatial working memory. Journal of Neurophysiology, 75, 454468.Google Scholar
Suleiman, A., Johnson, M., Shirtcliff, E., and Galván, A. (2015). School-based sex education and neuroscience: what we know about sex, romance, marriage, and adolescent brain development. Journal of School Health, 85, 567574.Google Scholar
Takahashi, Y., Roesch, M., Stalnaker, T., Haney, R., Calu, D., Taylor, A., and Schoenbaum, G. (2009). The orbitofrontal cortex and ventral tegmental area are necessary for learning from unexpected outcomes. Neuron, 62, 269280.CrossRefGoogle ScholarPubMed
Tamm, L., Menon, V., and Reiss, A. L. (2002). Maturation of brain function associated with response inhibition. Journal of the American Academy of Child and Adolescent Psychiatry, 41, 12311238.CrossRefGoogle ScholarPubMed
Tanaka, J., and Farah, M. (1993). Parts and wholes in face recognition. Quarterly Journal of Experimental Psychology A, 46, 225245.Google Scholar
Tantam, D., Monaghan, L., Nicholson, H., and Stirling, J. (1989). Autistic children's ability to interpret faces: a research note. Journal of Child Psychology and Psychiatry, 30, 623630.Google Scholar
Teicher, M., Andersen, S., and Hostetter, J.C. (1995). Evidence for dopamine receptor pruning between adolescence and adulthood in striatum but not nucleus accumbens. Developmental Brain Research, 89, 167172.Google Scholar
Teles, M., Silveira, L., Tusset, C., and Latronico, A. (2011). New genetic factors implicated in human GnRH-dependent precocious puberty: the role of kisspeptin system. Molecular Cell Endocrinology, 346(12), 8490.Google Scholar
Telzer, E., Fuligni, A., Lieberman, M., and Galván, A. (2014). Neural sensitivity to eudaimonic and hedonic rewards differentially predict adolescent depressive symptoms over time. Proceedings of the National Academy of Sciences USA, 111, 66006605.Google Scholar
Thomas, K.M., Drevets, W.C., Dahl, R.E., Ryan, N.D., Birmaher, B., Eccard, C.H., and Casey, B.J. (2001). Amygdala response to fearful faces in anxious and depressed children. Archives of General Psychiatry, 58, 10571063.Google Scholar
Thompson, P., Hayashi, K., Sowell, E., Gogtay, N., Giedd, J., Rapoport, J., de Zubicaray, G.I., Janke, A.L, Rose, S.E., Semple, J., Doddrell, D.M., Yang, Y., van Erp, T.G., Cannon, , and Toga, A. (2004). Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia. Neuroimage, 23, S2S18.Google Scholar
Thompson, R.A., and Nelson, C.A. (2001). Developmental science and the media. Early brain development. American Psychologist, 56(1), 515.Google Scholar
Thorell, L., Lindqvist, S., Bergman Nutley, S., Bohlin, G., and Klingberg, T. (2009). Training and transfer effects of executive functions in preschool children. Developmental Science, 12, 106113.Google Scholar
Todd, M., Nystrom, L., and Cohen, J. (2013). Confounds in multivariate pattern analysis: theory and rule representation case study. Neuroimage, 77, 157165.Google Scholar
Toldi, J., Rojik, I., and Feher, O. (1994). Neonatal monocular enucleation-induced cross-modal effects observed in the cortex of adult rat. Neuroscience, 62, 105114.Google Scholar
Tolson, K., and Chappell, P. (2012). The changes they are a-timed: metabolism, endogenous clocks, and the timing of puberty. Frontiers in Endocrinology (Lausanne), 3, 45.Google Scholar
Torres, O., Tejeda, H., Natividad, L., and O'Dell, L. (2008). Enhanced vulnerability to the rewarding effects of nicotine during the adolescent period of development. Pharmacology, Biochemistry and Behavior, 90, 658663.CrossRefGoogle Scholar
Tottenham, N. (2014). The importance of early experiences for neuro-affective development. Current Topics in Behavioral Neuroscience, 16, 109129.Google Scholar
Tottenham, N., Hare, T., and Casey, B. (2009). A developmental perspective on human amygdala function. In Whalen, P. and Phelps, E. (eds.), The human amygdala (pp. 107117). New York: The Guilford Press.Google Scholar
Tottenham, N., Hare, T.A., Milner, A., Gilhooly, T., Zevin, J.D., and Casey, B.J. (2011). Elevated amygdala response to faces following early deprivation. Developmental Science, 1, 4661.Google Scholar
Tottenham, N., Hare, T., Quinn, B., McCarry, T., Nurse, M., Gilhooly, T., Milner, A., Galván, A., Davidson, M.C., Eigsti, I.M., Thomas, K.M., Freed, P.J., Booma, E.S., Gunnar, M.R., Altemus, M., Aronson, J., and Casey, B. (2010). Prolonged institutional rearing is associated with atypically large amygdala volume and difficulties in emotion regulation. Developmental Science, 13, 4661.Google Scholar
Treadway, M., Buckholtz, J., Cowan, R., Woodward, N., Li, R., Ansari, M., Baldwin, R.M., Schwartzmann, A.N., Kessler, R.M., and Zald, D. (2012). Dopaminergic mechanisms of individual differences in human effort-based decision-making. Journal of Neuroscience, 32, 61706176.Google Scholar
Treit, S., Chen, Z., Rasmussen, C., and Beaulieu, C. (2014). White matter correlates of cognitive inhibition during development: a diffusion tensor imaging study. Neuroscience, 276, 8797.Google Scholar
Turkheimer, E., Haley, A., Waldron, M., D'Onofrio, B., and Gottesman, I. (2003). Socioeconomic status modifies heritability of IQ in young children. Psychological Science, 14, 623628.Google Scholar
Tymula, A., Rosenberg Belmaker, L., Roy, A., Ruderman, L., Manson, K., Glimcher, P., and Levy, I. (2012). Adolescents’ risk-taking behavior is driven by tolerance to ambiguity. Proceedings of the National Academy of Sciences USA, 109, 17,135–17,140.Google Scholar
UN (2011). The state of the world's children 2011. Adolescence: an age of opportunity. New York, United Nations Children's Fund, 2011; Emerging issues in adolescent health. Journal of Adolescent Health, 52, S1S45.Google Scholar
UN (2012). The Lancet Series on Adolescent Health. The Lancet.Google Scholar
Urberg, K. (1992). Locus of peer influence: social crowd and best friend. Journal of Youth and Adolescence, 21, 439450.Google Scholar
Urošević, S., Collins, P., Muetzel, R., Lim, K., and Luciana, M. (2012). Longitudinal changes in behavioral approach system sensitivity and brain structures involved in reward processing during adolescence. Developmental Psychology, 48, 14881500.Google Scholar
van den Bos, W., Cohen, M., Kahnt, T., and Crone, E. (2012). Striatum-medial prefrontal cortex connectivity predicts developmental changes in reinforcement learning. Cerebral Cortex, 22, 12471255.CrossRefGoogle ScholarPubMed
van der Geest, J., Kemner, C., Verbaten, M., and van Engeland, H. (2002). Gaze behavior of children with pervasive developmental disorder toward human faces: a fixation time study. Journal of Psychology and Psychiatry, 43, 669678.CrossRefGoogle ScholarPubMed
van der Meer, L., Groenewold, N., Nolen, W., Pijnenborg, M., and Aleman, A. (2011). Inhibit yourself and understand the other: neural basis of distinct processes underlying Theory of Mind. Neuroimage, 56(4), 23642374.Google Scholar
van Dijk, K., Sabuncu, M., and Buckner, R. (2012). The influence of head motion on intrinsic functional connectivity. Neuroimage, 59, 431438.CrossRefGoogle ScholarPubMed
van Duijvenvoorde, A., and Crone, E. (2013). The teenage brain: a neuroeconomic approach to adolescent decision making. Current Directions in Psychological Science, 22, 108113.Google Scholar
van Duijvenvoorde, A., Jansen, B., Bredman, J., and Huizenga, H. (2012). Age-related changes in decision making: comparing informed and noninformed situations. Developmental Psychology, 48, 192203.Google Scholar
van Duijvenvoorde, A.C., Op de Macks, Z.A., Overgaauw, S., Gunther Moor, B., Dahl, R.E., and Crone, E.A. (2014). A cross-sectional and longitudinal analysis of reward-related brain activation: effects of age, pubertal stage, and reward sensitivity. Brain and Cognition, 89, 314.CrossRefGoogle ScholarPubMed
Van Leijenhorst, L., Crone, E., and van der Molen, M. (2007). Developmental trends for object and spatial working memory: a psychophysiological analysis. Child Development, 78, 9871000.Google Scholar
van Leijenhorst, L., Moor, B., Op de Macks, Z., Rombouts, S., Westenberg, P., and Crone, E. (2010a). Adolescent risky decision-making: neurocognitive development of reward and control regions. Neuroimage, 51, 345355.Google Scholar
van Leijenhorst, L., Zanolie, K., van Meel, C., Westenberg, P., Rombouts, S., and Crone, E. (2010b). What motivates the adolescent? Brain regions mediating reward sensitivity across adolescents. Cerebral Cortex, 20, 6169.Google Scholar
van Praag, H., Shubert, T., Zhao, C., and Gage, F. (2005). Exercise enhances learning and hippocampal neurogenesis in aged mice. Journal of Neuroscience, 25, 86808685.Google Scholar
Varlinskaya, E., and Spear, L. (2008). Social interactions in adolescent and adult Sprague-Dawley rats: impact of social deprivation and test context familiarity. Behavioral Brain Research, 188, 398405.Google Scholar
Vasilyeva, M., Waterfall, H., and Huttenlocher, J. (2008). Emergence of syntax: commonalities and differences across children. Developmental Science, 11, 8497.Google Scholar
Vidal, C., Rapoport, J., Hayashi, K., Geaga, J., Sui, Y., McLemore, L., Alaghband, Y., Giedd, J.N., Gochman, P., Blumenthal, J., Gogtay, N., Nicolson, R., Toga, A.W., and Thompson, P. (2006). Dynamically spreading frontal and cingulate deficits mapped in adolescents with schizophrenia. Archives of General Psychiatry, 63, 2534.Google Scholar
Voas, R., Torres, P., Romano, E., and Lacey, J. (2012). Alcohol-related risk of driver fatalities: an update using 2007 data. Journal of Studies on Alcohol and Drugs, 73, 341350.Google Scholar
Volgyi, B., Farkas, T., and Toldi, J. (1993). Compensation of a sensory deficit inflicted upon newborn and adult animals. A behavioural study. Neuroreport, 4, 827829.Google Scholar
Volkow, N., Wang, G., Fowler, F., and Tomasi, D. (2012). Addiction circuitry in the human brain. Annual Review of Pharmacology and Toxicology, 52, 321336.Google Scholar
Volman, I., Toni, I., Verhagen, L., and Roelofs, K. (2011). Endogenous testosterone modulates prefrontal–amygdala connectivity during social emotional behavior. Cerebral Cortex, 21, 22822290.Google Scholar
Vorona, R., Szklo-Coxe, M., Wu, A., Dubik, M., Zhao, Y., and Catesby Ware, J. (2011). Dissimilar teen crash rates in two neighboring southeastern Virginia cities with different high school start times. Journal of Clinical Sleep Medicine, 7, 145151.Google Scholar
Voss, H., and Schiff, N. (2009). MRI of neuronal network structure, function, and plasticity. Progress in Brain Research, 175, 483496.Google Scholar
Voss, P., Collignon, D., Lassonde, M., and Lepore, F. (2010). Adaptation to sensory loss. Wiley Interdisciplinary Review of Cognitive Science, 1, 308328.Google Scholar
Vyas, A., Mitra, R., Shankaranarayana Rao, B., and Chattarji, S. (2002). Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons. Journal of Neuroscience, 22, 68106818.CrossRefGoogle ScholarPubMed
Wager, T., Davidson, M., Hughes, B., Lindquist, M., and Ochsner, K. (2008). Prefrontal-subcortical pathways mediating successful emotion regulation. Neuron, 59, 10371050.Google Scholar
Wahlstrohm, K. (2002). Changing times: findings from the first longitudinal study of later high school start times. National Association of Secondary School Principlies (NASSP) Bulletin, 286, 321.Google Scholar
Wahlstrohm, K., Dretzke, B., Gordon, M., Peterson, K., Edwards, K., and Gdula, J. (2014). Examining the impact of later school start times on the health and academic performance of high school students: a multi-site study. Center for Applied Research and Educational Improvement. St. Paul: University of Minnesota.Google Scholar
Walden, T., and Field, T. (1982). Discrimination of facial expressions by preschool children. Child Development, 53, 13121319.Google Scholar
Wang, A., Dapretto, M., Hariri, A., Sigman, M., and Bookheimer, S. (2004). Neural correlates of facial affect processing in children and adolescents with autism spectrum disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 43, 481490.CrossRefGoogle ScholarPubMed
Warneken, F., and Tomasello, M. (2006). Altruistic helping in human infants and young chimpanzees. Science, 311, 13011303.Google Scholar
Warneken, F., and Tomasello, M. (2008). Extrinsic rewards undermine altruistic tendencies in 20-month-olds. Developmental Psychology, 44, 17851788.CrossRefGoogle ScholarPubMed
Warneken, F., and Tomasello, M. (2009). Varieties of altruism in children and chimpanzees. Trends in Cognitive Neuroscience, 13, 397402.Google Scholar
Warneken, F., and Tomasello, M. (2013). The emergence of contingent reciprocity in young children. Journal of Experimental Child Psychology, 116, 338350.Google Scholar
Warren, M., and Vu, C. (2003). Central causes of hypogonadism – functional and organic. Endocrinology Metabolism Clinics of North America, 32(3), 593612.Google Scholar
Watanabe, Y., Gould, E., and McEwen, B. (1992). Stress induces atrophy of apical dendrites of hippocampal CA3 pyramidal neurons. Brain Research, 588, 341345.CrossRefGoogle ScholarPubMed
Waylen, A., and Wolke, D. (2004). Sex ’n’ drugs ’n’ rock ’n’ roll: the meaning and social consequences of pubertal timing. European Journal of Endocrinology, 151 Suppl. 3, U151U159.Google Scholar
Weeks, S., and Hobson, R. (1987). The salience of facial expression for autistic children. Journal of Child Psychology and Psychiatry, 28, 137151.Google Scholar
Weisleder, A., and Fernald, A. (2013). Talking to children matters: early language experience strengthens processing and builds vocabulary. Psychological Science, 24, 21432152.Google Scholar
Wellman, H., Lopez-Duran, S., LaBounty, J., and Hamilton, B. (2008). Infant attention to intentional action predicts preschool theory of mind. Developmental Psychology, 44, 618623.Google Scholar
Westerberg, H., and Klingberg, T. (2007). Changes in cortical activity after training of working memory – a single-subject analysis. Physiology and Behavior, 92, 186192.CrossRefGoogle ScholarPubMed
Westlake, E., and Boyle, L. (2012). Perceptions of driver distraction among teenage drivers. Transportation Research, Part F, 15, 644653.CrossRefGoogle Scholar
Whalen, P., Kagan, J., Cook, R., Davis, F., Kim, H., Polis, S., McLaren, D.G., Somerville, L.H., McLean, A.A., Maxwel, J.S., and Johnstone, T. (2004). Human amygdala responsivity to masked fearful eye whites. Science, 306, 2061.Google Scholar
Whalen, P., Rauch, S., Etcoff, N., McInerney, S., Lee, M., and Jenike, M. (1998). Masked presentations of emotional facial expressions modulate amygdala activity without explicit knowledge. Journal of Neuroscience, 18, 411418.Google Scholar
Wiesel, T., and Hubel, D. (1963). Single cell responses in striate cortex of kittens deprived of vision in one eye. Journal of Neurophysiology, 26, 10031017.Google Scholar
Will, G., van Lier, P., Crone, E., and Guroglu, B. (2016). Chronic childhood peer rejection is associated with heightened neural responses to social exclusion during adolescence. Journal of Abnormal Psychology, 44, 4355.Google Scholar
Williams, A. (2006). Young driver risk factors: successful and unsuccessful approaches for dealing with them and an agenda for the future. Injury and Prevention, 12, 48.Google Scholar
Williams, J., Waiter, G., Gilchrist, A., Perrett, D., Murray, A., and Whiten, A. (2006). Neural mechanisms of imitation and “mirror neuron” functioning in autism spectrum disorder. Neuropsychologia, 44, 610621.CrossRefGoogle Scholar
Wilmouth, C., and Spear, L. (2009). Hedonic sensitivity in adolescent and adult rats: taste reactivity and voluntary sucrose consumptio. Pharmacology, Biochemistry and Behavior, 92, 566573.Google Scholar
Wong, W., Nicolson, M., Stuff, J., Butte, N., Ellis, K., Hergenroeder, A., and Smith, E. (1998). Serum leptin concentrations in Caucasian and African-American girls. Journal of Clinical Endocrinology and Metabolism, 83, 35743577.Google Scholar
Woolley, C., Gould, E., and McEwen, B. (1990). Exposure to excess glucocorticoids alters dendritic morphology of adult hippocampal pyramidal neurons. Brain Research, 531, 225231.Google Scholar
Wu, T., Mendola, P., and Buck, G. (2002). Ethnic differences in the presence of secondary sex characteristics and menarche among US girls: the Third National Health and Nutrition Examination Survey, 1988–1994. Pediatrics, 110, 752757.Google Scholar
Zatorre, R., Chen, J., and Penhune, V. (2007). When the brain plays music: auditory–motor interactions in music perception and production. Nature Reviews Neuroscience, 8, 547558.Google Scholar
Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L., and Friedman, J. (1994). Positional cloning of the mouse obese gene and its human homologue. Nature, 372, 425432.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Complete List of References
  • Adriana Galván, University of California, Los Angeles
  • Book: The Neuroscience of Adolescence
  • Online publication: 15 September 2018
  • Chapter DOI: https://doi.org/10.1017/9781316106143.011
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Complete List of References
  • Adriana Galván, University of California, Los Angeles
  • Book: The Neuroscience of Adolescence
  • Online publication: 15 September 2018
  • Chapter DOI: https://doi.org/10.1017/9781316106143.011
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Complete List of References
  • Adriana Galván, University of California, Los Angeles
  • Book: The Neuroscience of Adolescence
  • Online publication: 15 September 2018
  • Chapter DOI: https://doi.org/10.1017/9781316106143.011
Available formats
×