Pediatric neuroimaging studies 1-5 , up to now exclusively cross sectional, identify linear decreases in cortical gray matter and increases in white matter across ages 4 to 20. In this large-scale longitudinal pediatric neuroimaging study, we confirmed linear increases in white matter, but demonstrated nonlinear changes in cortical gray matter, with a preadolescent increase followed by a postadolescent decrease. These changes in cortical gray matter were regionally specific, with developmental curves for the frontal and parietal lobe peaking at about age 12 and for the temporal lobe at about age 16, whereas cortical gray matter continued to increase in the occipital lobe through age 20.The subjects for this study were healthy boys and girls participating in an ongoing longitudinal pediatric brain-MRI project at the Child Psychiatry Branch at the National Institute of Mental Health. Subjects were recruited from the community as previously described, using phone screening, questionnaires mailed to parents and teachers and face-to-face physical and psychological testing; approximately one in six volunteers were accepted 5 . At least 1 scan was obtained from each of 145 healthy subjects (89 male). Of these, 65 had at least 2 scans, 30 had at least 3 scans, 2 had at least 4 scans and 1 had 5 scans, acquired at approximately two-year intervals. The age range was from 4.2 to 21.6 years. There were no significant sex differences for age, Tanner stage, ethnicity, socioeconomic status, height, weight or handedness.All subjects were scanned on the same GE 1.5 Tesla Signa scanner using the same three-dimensional, spoiled-gradient, recalled echo in the steady state (3D SPGR) imaging protocol, with an axial-slice thickness of 1.5 mm, a time-to-echo of 5 ms, a repetition time of 24 ms, flip angle of 45°, a 192 ( 256 acquisition matrix, 1 excitation and a field of view of 24 cm. A clinical neuroradiologist evaluated all scans; no gross abnormalities were reported.Volumes of white and cortical gray matter were quantitatively analyzed by combining a technique using an artificial neural network to classify tissues based on voxel intensity with non-linear registration to a template brain for which these tissue regions had been manually defined 7 . This technique supplemented MRI signal-intensity information with predetermined brain anatomy and provides lobar (frontal, parietal, temporal and occipital) parcellation of cortical gray-and white-matter volumes.We used previously described statistical analysis techniques that combine cross-sectional and longitudinal data 8 . These longitudinal methods are more sensitive to detecting individual growth patterns, even in the presence of large interindividual variation 9 . We assessed if there was significant change with age, if developmental curves differed by sex and/or region and whether the developmental curves were linear or quadratic.The volume of white matter increased linearly with age ( Fig. 1; Table 1), increasing less in females than in males. The net increase across ages 4 to 22 w...

What do we know about the maturation of the human brain during adolescence? Do structural changes in cerebral cortex reflect synaptic pruning? Are increases in white-matter volume driven by myelination? Is the adolescent brain more or less sensitive to reward? These are but a few questions we ask in this review while attempting to indicate how findings obtained in the healthy brain help in furthering our understanding of mental health during adolescence.