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Link to original content: https://doi.org/10.1038/nrn2513
Why do many psychiatric disorders emerge during adolescence? | Nature Reviews Neuroscience
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Why do many psychiatric disorders emerge during adolescence?

Abstract

The peak age of onset for many psychiatric disorders is adolescence, a time of remarkable physical and behavioural changes. The processes in the brain that underlie these behavioural changes have been the subject of recent investigations. What do we know about the maturation of the human brain during adolescence? Do structural changes in the cerebral cortex reflect synaptic pruning? Are increases in white-matter volume driven by myelination? Is the adolescent brain more or less sensitive to reward? Finding answers to these questions might enable us to further our understanding of mental health during adolescence.

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Figure 1: Schematic representations of developmental trajectories in local volume of cortical grey matter, glucose metabolism and synaptic density.
Figure 2: Sexual dimorphism in the maturation of white matter during adolescence.
Figure 3: Functional connectivity correlates with resistance to peer influence.
Figure 4: Ranges of onset age for common psychiatric disorders.

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References

  1. Bushong, S. Magnetic Resonance Imaging 3rd edn (Mosby, Inc., 2003).

    Google Scholar 

  2. Roberts, T. P. & Mikulis, D. Neuro MR: principles. J. Magn. Reson. Imaging 26, 823–837 (2007).

    Article  PubMed  Google Scholar 

  3. Keshavan, M. S., Kapur, S. & Pettegrew, J. W. Magnetic resonance spectroscopy in psychiatry: potential, pitfalls and promise. Am. J. Psychiatry 148, 976–985 (1991).

    Article  CAS  PubMed  Google Scholar 

  4. Logothetis, N. K., Pauls, J., Augath, M., Trinath, T. & Oeltermann, A. Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150–157 (2001).

    Article  CAS  PubMed  Google Scholar 

  5. Lenroot, R. K. & Giedd, J. N. Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci. Biobehav. Rev. 30, 718–729 (2006).

    Article  PubMed  Google Scholar 

  6. Paus, T. Mapping brain maturation and cognitive development during adolescence. Trends Cogn. Sci. 9, 60–68 (2005).

    Article  PubMed  Google Scholar 

  7. Giedd, J. N., Blumenthal, J. & Jeffries, N. O. et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nature Neurosci. 2, 861–863 (1999).

    Article  CAS  PubMed  Google Scholar 

  8. Gogtay, N. et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc. Natl Acad. Sci. USA 101, 8174–8179 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Sowell, E. R. et al. Mapping cortical change across the human life span. Nature Neurosci. 6, 309–315 (2003).

    Article  CAS  PubMed  Google Scholar 

  10. Pfefferbaum, A. et al. A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Arch. Neurol. 51, 874–887 (1994).

    Article  CAS  PubMed  Google Scholar 

  11. DeBellis, M. D. et al. Sex differences in brain maturation during childhood and adolescence. Cereb. Cortex 11, 552–557 (2001).

    Article  CAS  Google Scholar 

  12. Klingberg, T., Vaidya, C. J., Gabrieli, J. D., Moseley, M. E. & Hedehus, M. Myelination and organization of the frontal white matter in children: a diffusion tensor MRI study. Neuroreport 10, 2817–2821 (1999).

    Article  CAS  PubMed  Google Scholar 

  13. Schmithorst, V. J., Wilke, M., Dardzinski, B. J. & Holland, S. K. Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. Radiology 222, 212–218 (2002).

    Article  PubMed  Google Scholar 

  14. Snook, L., Paulson, L. A., Roy, D., Phillips, L. & Beaulieu, C. Diffusion tensor imaging of neurodevelopment in children and young adults. Neuroimage 26, 1164–1173 (2005).

    Article  PubMed  Google Scholar 

  15. Steinberg, L. et al. Age differences in sensation seeking and impulsivity as indexed by behaviour and self-report: evidence for a dual systems model. Dev. Psychol. (in the press).

  16. Kwon, H., Reiss, A. L. & Menon, V. Neural basis of protracted developmental changes in visuo-spatial working memory. Proc. Natl Acad. Sci. USA 99, 13336–13341 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Adleman, N. E. et al. A developmental fMRI study of the Stroop color-word task. Neuroimage 16, 61–75 (2002).

    Article  PubMed  Google Scholar 

  18. Luna, B. et al. Maturation of widely distributed brain function subserves cognitive development. Neuroimage 13, 786–793 (2001).

    Article  CAS  PubMed  Google Scholar 

  19. Rubia, K. et al. Functional frontalisation with age: mapping neurodevelopmental trajectories with fMRI. Neurosci. Biobehav. Rev. 24, 13–19 (2000).

    Article  CAS  PubMed  Google Scholar 

  20. Tamm, L., Menon, V. & Reiss, A. L. Maturation of brain function associated with response inhibition. J. Am. Acad. Child Adolesc. Psychiatry 41, 1231–1238 (2002).

    Article  PubMed  Google Scholar 

  21. Bunge, S. A., Dudukovic, N. M., Thomason, M. E., Vaidya, C. J. & Gabrieli, J. D. Immature frontal lobe contributions to cognitive control in children: evidence from fMRI. Neuron 33, 301–311 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Steinberg, L. A neurobehavioral perspective on adolescent risk-taking. Dev. Rev. 28, 78–106 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Robbins, T. W. & Everitt, B. J. Neurobehavioural mechanisms of reward and motivation. Curr. Opin. Neurobiol. 6, 228–236 (1996).

    Article  CAS  PubMed  Google Scholar 

  24. Galvan, A. et al. Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk-taking behavior in adolescents. J. Neurosci. 26, 6885–6892 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ernst, M. Amygdala and nucleus accumbens in responses to receipt and omission of gains in adults and adolescents. Neuroimage 25, 1279–1291 (2005).

    Article  PubMed  Google Scholar 

  26. Bjork, J. M. et al. Incentive-elicited brain activation in adolescents: similarities and differences from young adults. J. Neurosci. 24, 1793–1802 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Purves, D., White, L. E. & Riddle, D. R. Is neural development Darwinian? Trends Neurosci. 19, 460–464 (1996).

    Article  CAS  PubMed  Google Scholar 

  28. Huttenlocher, P. R. & de Courten, C. The development of synapses in striate cortex of man. Hum. Neurobiol. 6, 1–9 (1987).

    CAS  PubMed  Google Scholar 

  29. Huttenlocher, P. R. Synapse elimination and plasticity in developing human cerebral cortex. Am. J. Ment. Defic. 88, 488–496 (1984).

    CAS  PubMed  Google Scholar 

  30. Huttenlocher, P. R. & Dabholkar, A. S. Regional differences in synaptogenesis in human cerebral cortex. J. Comp. Neurol. 387, 167–178 (1997).

    Article  CAS  PubMed  Google Scholar 

  31. Rakic, P., Bourgeois, J. P., Eckenhoff, M. F., Zecevic, N. & Goldman-Rakic, P. S. Concurrent overproduction of synapses in diverse regions of the primate cerebral cortex. Science 232, 232–235 (1986).

    Article  CAS  PubMed  Google Scholar 

  32. Bourgeois, J. P. & Rakic, P. Changes of synaptic density in the primary visual cortex of the macaque monkey from fetal to adult stage. J. Neurosci. 13, 2801–2820 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Braitenberg, V. & Schuz, A. Cortex: statistics and geometry of neuronal connectivity (Springer, Heidelberg, 1998).

    Book  Google Scholar 

  34. Kaes, T. Die Grosshirnrinde des Menschen in ihren Massen und ihrem Fasergehalt (Fisher, Jena, 1907).

    Google Scholar 

  35. Conel, J. Postnatal development of the human cerebral cortex: the cortex of the seventy- two- month infant. Vol. 8. (Harvard Univ. Press, Cambridge, Massachusetts, 1967).

    Google Scholar 

  36. Yakovlev, P. & Lecours, A. in Regional Development of the Brain in Early Life (ed. Minkowski, A.) 3–70 (Blackwell Scientific, Oxford, 1967).

    Google Scholar 

  37. Perrin, J. et al. Growth of white matter in the adolescent brain: role of testosterone and androgen receptor. J. Neurosci. 28, 9519–9524 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Paus, T. in Handbook of Brain Connectivity (eds Jirsa, V. & McIntosh, A. R.) 463−476 (Springer, New York, 2007).

    Book  Google Scholar 

  39. Menon, V., Boyett-Anderson, J. M. & Reiss, A. L. Maturation of medial temporal lobe response and connectivity during memory encoding. Brain Res. Cogn. Brain Res. 25, 379–385 (2005).

    Article  CAS  PubMed  Google Scholar 

  40. Grosbras, M. H. et al. Neural mechanisms of resistance to peer influence in early adolescence. J. Neurosci. 27, 8040–8045 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Rizzolatti, G. & Craighero, L. The mirror-neuron system. Annu. Rev. Neurosci. 27, 169–192 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Puce, A. & Perrett, D. Electrophysiology and brain imaging of biological motion. Philos. Trans. R. Soc. Lond. B Biol. Sci. 358, 435–445 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Petrides, M. Lateral prefrontal cortex: architectonic and functional organization. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360, 781–795 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Steinberg, L. & Monahan, K. C. Age differences in resistance to peer influence. Dev. Psychol. 43, 1531–1543 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Tseng, K. Y. & O'Donnell, P. Dopamine modulation of prefrontal cortical interneurons changes during adolescence. Cereb. Cortex 17, 1235–1240 (2007).

    Article  PubMed  Google Scholar 

  46. Erickson, S. L., Akil, M., Levey, A. I. & Lewis, D. A. Postnatal development of tyrosine hydroxylase- and dopamine transporter-immunoreactive axons in monkey rostral entorhinal cortex. Cereb. Cortex 8, 415–427 (1998).

    Article  CAS  PubMed  Google Scholar 

  47. Rosenberg, D. R. & Lewis, D. A. Postnatal maturation of the dopaminergic innervation of monkey prefrontal and motor cortices: a tyrosine hydroxylase immunohistochemical analysis. J. Comp. Neurol. 358, 383–400 (1995).

    Article  CAS  PubMed  Google Scholar 

  48. Tunbridge, E. M. et al. Catechol-o-methyltransferase enzyme activity and protein expression in human prefrontal cortex across the postnatal lifespan. Cereb. Cortex 17, 1206–1212 (2007).

    Article  CAS  PubMed  Google Scholar 

  49. Weickert, C. S. et al. Postnatal alterations in dopaminergic markers in the human prefrontal cortex. Neuroscience 144, 1109–1119 (2007).

    Article  CAS  PubMed  Google Scholar 

  50. Kessler, R. C. et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62, 593–602 (2005).

    Article  PubMed  Google Scholar 

  51. Hafner, H. et al. How does gender influence age at first hospitalization for schizophrenia? A transnational case register study. Psychol. Med. 19, 903–918 (1989).

    Article  CAS  PubMed  Google Scholar 

  52. Kyriakopoulos, M. & Frangou, S. Pathophysiology of early onset schizophrenia. Int. Rev. Psychiatry 19, 315–324 (2007).

    Article  PubMed  Google Scholar 

  53. Feinberg, I. Schizophrenia: caused by a fault in programmed synaptic elimination during adolescence? J. Psychiatr. Res. 17, 319–334 (1982–1983).

    Article  PubMed  Google Scholar 

  54. Keshavan, M. S., Anderson, S. & Pettegrew, J. W. Is schizophrenia due to excessive synaptic pruning in the prefrontal cortex? The Feinberg hypothesis revisited. J. Psychiatr. Res. 28, 239–265 (1994).

    Article  CAS  PubMed  Google Scholar 

  55. Keshavan, M. S. et al. Delta sleep deficits in schizophrenia: evidence from automated analyses of sleep data. Arch. Gen. Psychiatry 55, 443–448 (1998).

    Article  CAS  PubMed  Google Scholar 

  56. Pettegrew, J. W. et al. Alterations in brain high-energy phosphate and membrane phospholipid metabolism in first-episode, drug-naive schizophrenics. A pilot study of the dorsal prefrontal cortex by in vivo phosphorus 31 nuclear magnetic resonance spectroscopy. Arch. Gen. Psychiatry 48, 563–568 (1991).

    Article  CAS  PubMed  Google Scholar 

  57. Andreasen, N. C. et al. Hypofrontality in neuroleptic-naive patients and in patients with chronic schizophrenia. Assessment with xenon 133 single-photon emission computed tomography and the Tower of London. Arch. Gen. Psychiatry 49, 943–958 (1992).

    Article  CAS  PubMed  Google Scholar 

  58. Sporn, A. L. et al. Progressive brain volume loss during adolescence in childhood-onset schizophrenia. Am. J. Psychiatry 160, 2181–2189 (2003).

    Article  PubMed  Google Scholar 

  59. Garey, L. J. et al. Reduced dendritic spine density on cerebral cortical pyramidal neurons in schizophrenia. J. Neurol. Neurosurg. Psychiatr. 65, 446–453 (1998).

    Article  CAS  Google Scholar 

  60. Selemon, L. D., Rajkowska, G. & Goldman-Rakic, P. S. Abnormally high neuronal density in the schizophrenic cortex. A morphometric analysis of prefrontal area 9 and occipital area 17. Arch. Gen. Psychiatry 52, 805–818; discussion 819–820 (1995).

    Article  CAS  PubMed  Google Scholar 

  61. Eastwood, S. L. & Harrison, P. J. Decreased synaptophysin in the medial temporal lobe in schizophrenia demonstrated using immunoautoradiography. Neuroscience 69, 339–343 (1995).

    Article  CAS  PubMed  Google Scholar 

  62. Maggs, J. L., Patrick, M. E. & Feinstein, L. Childhood and adolescent predictors of alcohol use and problems in adolescence and adulthood in the National Child Development Study. Addiction 103 (Suppl. 1), 7–22 (2008).

    Article  PubMed  Google Scholar 

  63. Chambers, R. A., Taylor, J. R. & Potenza, M. N. Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. Am. J. Psychiatry 160, 1041–1052 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Kandel, D. B., Yamaguchi, K. & Chen, K. Stages of progression in drug involvement from adolescence to adulthood: further evidence for the gateway theory. J. Stud. Alcohol 53, 447–457 (1992).

    Article  CAS  PubMed  Google Scholar 

  65. Cloninger, C. R., Sigvardsson, S. & Bohman, M. Childhood personality predicts alcohol abuse in young adults. Alcohol. Clin. Exp. Res. 12, 494–505 (1988).

    Article  CAS  PubMed  Google Scholar 

  66. Wills, T. A., Vaccaro, D. & McNamara, G. Novelty seeking, risk taking, and related constructs as predictors of adolescent substance use: an application of Cloninger's theory. J. Subst. Abuse 6, 1–20 (1994).

    Article  CAS  PubMed  Google Scholar 

  67. Adams, G., Montemayor, R. & Gullotta, T. Biology of adolescent behavior and development (Sage, Newbury Park, California, 1989).

    Google Scholar 

  68. Savin-Williams, R. Adolescence: an ethological perspective (Springer, New York, 1987).

    Book  Google Scholar 

  69. Bjork, J. M., Smith, A. R., Danube, C. L. & Hommer, D. W. Developmental differences in posterior mesofrontal cortex recruitment by risky rewards. J. Neurosci. 27, 4839–4849 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Levin, E. D., Rezvani, A. H., Montoya, D., Rose, J. E. & Swartzwelder, H. S. Adolescent-onset nicotine self-administration modeled in female rats. Psychopharmacology (Berl.) 169, 141–149 (2003).

    Article  CAS  Google Scholar 

  71. Spear, L. P. Alcohol's effects on adolescents. Alcohol Res. Health 26, 287–291 (2002).

    PubMed  PubMed Central  Google Scholar 

  72. White, A. M. et al. Differential effects of ethanol on motor coordination in adolescent and adult rats. Pharmacol. Biochem. Behav. 73, 673–677 (2002).

    Article  CAS  PubMed  Google Scholar 

  73. Doremus, T. L., Brunell, S. C., Varlinskaya, E. I. & Spear, L. P. Anxiogenic effects during withdrawal from acute ethanol in adolescent and adult rats. Pharmacol. Biochem. Behav. 75, 411–418 (2003).

    Article  CAS  PubMed  Google Scholar 

  74. Silveri, M. M. & Spear, L. P. The effects of NMDA and GABAA pharmacological manipulations on ethanol sensitivity in immature and mature animals. Alcohol. Clin. Exp. Res. 26, 449–456 (2002).

    Article  CAS  PubMed  Google Scholar 

  75. White, A. M. & Swartzwelder, H. S. Hippocampal function during adolescence: a unique target of ethanol effects. Ann. NY Acad. Sci. 1021, 206–220 (2004).

    Article  CAS  PubMed  Google Scholar 

  76. Li, Q., Wilson, W. A. & Swartzwelder, H. S. Differential effect of ethanol on NMDA EPSCs in pyramidal cells in the posterior cingulate cortex of juvenile and adult rats. J. Neurophysiol. 87, 705–711 (2002).

    Article  CAS  PubMed  Google Scholar 

  77. Brown, S. A. & Tapert, S. F. Adolescence and the trajectory of alcohol use: basic to clinical studies. Ann. NY Acad. Sci. 1021, 234–244 (2004).

    Article  PubMed  Google Scholar 

  78. De Bellis, M. D. et al. Hippocampal volume in adolescent-onset alcohol use disorders. Am. J. Psychiatry 157, 737–744 (2000).

    Article  CAS  PubMed  Google Scholar 

  79. Adriani, W. & Laviola, G. Windows of vulnerability to psychopathology and therapeutic strategy in the adolescent rodent model. Behav. Pharmacol. 15, 341–352 (2004).

    Article  CAS  PubMed  Google Scholar 

  80. Andersen, S. L. & Teicher, M. H. Stress, sensitive periods and maturational events in adolescent depression. Trends Neurosci. 31, 183–191 (2008).

    Article  CAS  PubMed  Google Scholar 

  81. Birmaher, B. & Axelson, D. Course and outcome of bipolar spectrum disorder in children and adolescents: a review of the existing literature. Dev. Psychopathol. 18, 1023–1035 (2006).

    Article  PubMed  Google Scholar 

  82. Beesdo, K. et al. Incidence of social anxiety disorder and the consistent risk for secondary depression in the first three decades of life. Arch. Gen. Psychiatry 64, 903–912 (2007).

    Article  PubMed  Google Scholar 

  83. Reinherz, H. Z., Paradis, A. D., Giaconia, R. M., Stashwick, C. K. & Fitzmaurice, G. Childhood and adolescent predictors of major depression in the transition to adulthood. Am. J. Psychiatry 160, 2141–2147 (2003).

    Article  PubMed  Google Scholar 

  84. Blumberg, H. P. et al. Amygdala and hippocampal volumes in adolescents and adults with bipolar disorder. Arch. Gen. Psychiatry 60, 1201–1208 (2003).

    Article  PubMed  Google Scholar 

  85. De Bellis, M. D. et al. Brain structures in pediatric maltreatment-related posttraumatic stress disorder: a sociodemographically matched study. Biol. Psychiatry 52, 1066–1078 (2002).

    Article  PubMed  Google Scholar 

  86. DelBello, M. P., Zimmerman, M. E., Mills, N. P., Getz, G. E. & Strakowski, S. M. Magnetic resonance imaging analysis of amygdala and other subcortical brain regions in adolescents with bipolar disorder. Bipolar Disord. 6, 43–52 (2004).

    Article  PubMed  Google Scholar 

  87. Thomas, K. M. et al. Amygdala response to fearful faces in anxious and depressed children. Arch. Gen. Psychiatry 58, 1057–1063 (2001).

    Article  CAS  PubMed  Google Scholar 

  88. Monk, C. S. et al. Adolescent immaturity in attention-related brain engagement to emotional facial expressions. Neuroimage 20, 420–428 (2003).

    Article  PubMed  Google Scholar 

  89. Angold, A. & Costello, E. J. Puberty and depression. Child Adolesc. Psychiatr. Clin. N. Am. 15, 919–937 (2006).

    Article  PubMed  Google Scholar 

  90. Hayward, C. & Sanborn, K. Puberty and the emergence of gender differences in psychopathology. J. Adolesc. Health 30 (4 Suppl.), 49–58 (2002).

    Article  PubMed  Google Scholar 

  91. Patton, G. C. et al. Menarche and the onset of depression and anxiety in Victoria, Australia. J. Epidemiol. Community Health 50, 661–666 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Shen, H. et al. Reversal of neurosteroid effects at α4β2δ GABAA receptors triggers anxiety at puberty. Nature Neurosci. 10, 469–477 (2007).

    Article  CAS  PubMed  Google Scholar 

  93. Shaw, P. et al. Intellectual ability and cortical development in children and adolescents. Nature 440, 676–679 (2006).

    Article  CAS  PubMed  Google Scholar 

  94. Wallace, G. L. et al. A pediatric twin study of brain morphometry. J. Child Psychol. Psychiatry 47, 987–993 (2006).

    Article  PubMed  Google Scholar 

  95. Schmitt, J. E. et al. A multivariate analysis of neuroanatomic relationships in a genetically informative pediatric sample. Neuroimage 35, 70–82 (2007).

    Article  PubMed  Google Scholar 

  96. Pausova, Z. et al. Genes, maternal smoking, and the offspring brain and body during adolescence: design of the Saguenay Youth Study. Hum. Brain Mapp. 28, 502–518 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Sisk, C. L. & Foster, D. L. The neural basis of puberty and adolescence. Nature Neurosci. 7, 1040–1047 (2004).

    Article  CAS  PubMed  Google Scholar 

  98. Shen, D. et al. Automated morphometric study of brain variation in XXY males. Neuroimage 23, 648–653 (2004).

    Article  PubMed  Google Scholar 

  99. Giedd, J. N. et al. Puberty-related influences on brain development. Mol. Cell. Endocrinol. 254255, 154–162 (2006).

    Article  CAS  PubMed  Google Scholar 

  100. Ernst, M. & Mueller, S. C. The adolescent brain: insights from functional neuroimaging research. Dev. Neurobiol. 68, 729–743 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Manganas, L. N. et al. Magnetic resonance spectroscopy identifies neural progenitor cells in the live human brain. Science 318, 980–985 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Steinberg, L. Cognitive and affective development in adolescence. Trends Cogn. Sci. 9, 69–74 (2005).

    Article  PubMed  Google Scholar 

  103. Arguello, P. A. & Gogos, J. A. Modeling madness in mice: one piece at a time. Neuron 52, 179–196 (2006).

    Article  CAS  PubMed  Google Scholar 

  104. Hursh, J. Conduction velocity and diameter of nerve fibers. Am. J. Physiol. 127, 131–139 (1939).

    Article  Google Scholar 

  105. Rushton, W. A. A theory of the effects of fibre size in medullated nerve. J. Physiol. 115, 101–122 (1951).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Schmidt-Nielson, K. Animal physiology: adaptation and environment 5th edn (Cambridge Univ. Press, 1997).

    Google Scholar 

  107. Eickhoff, S. B., Schleicher, A., Scheperjans, F., Palomero-Gallagher, N. & Zilles, K. Analysis of neurotransmitter receptor distribution patterns in the cerebral cortex. Neuroimage 34, 1317–1330 (2007).

    Article  PubMed  Google Scholar 

  108. Zilles, K., Palomero-Gallagher, N. & Schleicher, A. Transmitter receptors and functional anatomy of the cerebral cortex. J. Anat. 205, 417–432 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Chugani, H. T., Phelps, M. E. & Mazziotta, J. C. Positron-emission tomography study of human brain functional development. Ann. Neurol. 22, 487–497 (1987).

    Article  CAS  PubMed  Google Scholar 

  110. Huttenlocher, P. R. Synaptic density in human frontal cortex - developmental changes and effects of aging. Brain Res. 163, 195–205 (1979).

    Article  CAS  PubMed  Google Scholar 

  111. Rakic, P., Bourgeois, J. P. & Goldman-Rakic, P. S. Synaptic development of the cerebral cortex: implications for learning, memory, and mental illness. Prog. Brain Res. 102, 227–243 (1994).

    Article  CAS  PubMed  Google Scholar 

  112. Kessler, R. C. & Wang, P. S. The descriptive epidemiology of commonly occurring mental disorders in the United States. Annu. Rev. Public Health 29, 115–129 (2008).

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors' work is supported by the Canadian Institutes of Health Research (T.P.), the Royal Society, UK (T.P.) and the US National Institutes of Health (T.P., K.M. and J.N.G.).

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Correspondence to Tomáš Paus or Jay N. Giedd.

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Glossary

Androgen insensitivity syndrome

(Also known as androgen resistance syndrome or testicular feminization.) An X-linked, recessive condition characterized by a complete or partial failure of virilization that is due to a mutation on the gene that encodes the androgen receptor.

Anti-saccade task

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Diffusion tensor imaging

(DTI). An MRI-based technique that allows one to characterize the structural properties of white matter.

Eriksen flanker task

A task in which subjects have to respond to a stimulus that is flanked by other stimuli that may code an alternative response.

Familial male precocious puberty

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Founder effect

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(FA). The directionality of the (fast) diffusion of water in the extracellular space around the axons (in most common acquisition protocols). The more unidirectional the water diffusion is in a given fibre tract, the higher the FA value in that location.

Go/no-go task

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(MTR). A measure used for assessing white-matter properties; it provides information on the macromolecular content and structure of the tissue. Given that the macromolecules of myelin are the dominant source of MT signal in white matter, one can use MTR as an index of myelination. Note, however, that myelin is not likely to be the sole factor influencing the MTR.

Neural Darwinism

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Stop task

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Stroop task

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A set of regions, located along the superior temporal sulcus, that are involved in processing biological motion induced by the movement of different body parts, such as the eyes, the face or the entire body.

Tanner stage III

One of the five stages of puberty. Without resorting to a physical exam, pubertal stages can be assessed using, for example, the Puberty Development Scale, which is an eight-item self-report measure of physical development based on the Tanner stages with separate forms for males and females. For this scale there are five categories of pubertal status: prepubertal, beginning pubertal, midpubertal, advanced pubertal and postpubertal.

XXY

(Klinefelter's syndrome). A genetic syndrome that affects males and is caused by the presence of two X chromosomes (resulting in a 47-chromosome karotype).

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Paus, T., Keshavan, M. & Giedd, J. Why do many psychiatric disorders emerge during adolescence?. Nat Rev Neurosci 9, 947–957 (2008). https://doi.org/10.1038/nrn2513

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