Magnetic resonance imaging volumetry studies report inverted U-patterns with increasing white-matter (WM) volume into middle age suggesting protracted WM maturation compared with the cortical gray matter. Diffusion tensor imaging (DTI) is sensitive to degree and direction of water permeability in biological tissues, providing in vivo indices of WM microstructure. The aim of this cross-sectional study was to delineate age trajectories of WM volume and DTI indices in 430 healthy subjects ranging 8-85 years of age. We used automated regional brain volume segmentation and tract-based statistics of fractional anisotropy, mean, and radial diffusivity as markers of WM integrity. Nonparametric regressions were used to fit the age trajectories and to estimate the timing of maximum development and deterioration in aging. Although the volumetric data supported protracted growth into the sixth decade, DTI indices plateaued early in the fourth decade across all tested regions and then declined slowly into late adulthood followed by an accelerating decrease in senescence. Tractwise and voxel-based analyses yielded regional differences in development and aging but did not provide ample evidence in support of a simple last-in-first-out hypothesis of life-span changes.

The development of cortical gray matter, white matter (WM) volume, and WM microstructure in adolescence is beginning to be fairly well characterized by structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI) studies. However, these aspects of brain development have rarely been investigated concurrently in the same sample and hence the relations between them are not understood. We delineated the age-related changes in cortical thickness, regional WM volume, and diffusion characteristics and investigated the relationships between these properties of brain development. One hundred and sixty-eight healthy participants aged 8-30 years underwent sMRI and DTI. The results showed regional age-related cortical thinning, WM volume increases, and changes in diffusion parameters. Cortical thickness was the most strongly age-related parameter. All classes of measures showed unique associations with age. The results indicate that cortical thinning in adolescence cannot be explained by WM maturation in underlying regions as measured by volumetry or DTI. Moderate associations between cortical thickness and both volume and diffusion parameters in underlying WM regions were also found, although the relationships were not strong. It is concluded that none of the measures are redundant and that the integration of the 3 will yield a more complete understanding of brain maturation.

Brain development during late childhood and adolescence is characterized by decreases in gray matter (GM) and increases in white matter (WM) and ventricular volume. The dynamic nature of development across different structures is, however, not well understood, and the present magnetic resonance imaging study took advantage of a whole-brain segmentation approach to describe the developmental trajectories of 16 neuroanatomical volumes in the same sample of children, adolescents, and young adults (n ϭ 171; range, 8 -30 years). The cerebral cortex, cerebral WM, caudate, putamen, pallidum, accumbens area, hippocampus, amygdala, thalamus, brainstem, cerebellar GM, cerebellar WM, lateral ventricles, inferior lateral ventricles, third ventricle, and fourth ventricle were studied. The cerebral cortex was further analyzed in terms of lobar thickness and surface area. The results revealed substantial heterogeneity in developmental trajectories. GM decreased nonlinearly in the cerebral cortex and linearly in the caudate, putamen, pallidum, accumbens, and cerebellar GM, whereas the amygdala and hippocampus showed slight, nonlinear increases in GM volume. WM increased nonlinearly in both the cerebrum and cerebellum, with an earlier maturation in cerebellar WM. In addition to similarities in developmental trajectories within subcortical regions, our results also point to differences between structures within the same regions: among the basal ganglia, the caudate showed a weaker relationship with age than the putamen and pallidum, and in the cerebellum, differences were found between GM and WM development. These results emphasize the importance of studying a wide range of structural variables in the same sample, for a broader understanding of brain developmental principles.

Early-life development is characterized by dramatic changes, impacting lifespan function more than changes inany other period. Developmental origins of neurocognitive late-life functions are acknowledged, but detailed longitudinal magnetic resonance imaging studies of brain maturation and direct comparisons with aging are lacking. To these aims, a novel method was used to measure longitudinal volume changes in development (n = 85, 8–22 years) and aging (n = 142, 60–91 years). Developmental reductions exceeded 1% annually in much of cortex, more than double that seen in aging, with a posterior-to-anterior gradient. Cortical reductions were greater than subcortical during development, while the opposite held in aging. The pattern of lateral cortical changes was similar across development and aging, but the pronounced medial temporal reduction in aging was not precast in development. Converging patterns of change in adolescents and elderly, particularly in medial prefrontal areas, suggest that late developed cortices are especially vulnerable to atrophy in aging. A key question in future research will be to disentangle the neurobiological underpinnings for the differences and the similarities between brain changes in development and aging.

There is a growing realization that early life influences have lasting impact on brain function and structure. Recent research has demonstrated that genetic relationships in adults can be used to parcellate the cortex into regions of maximal shared genetic influence, and a major hypothesis is that genetically programmed neurodevelopmental events cause a lasting impact on the organization of the cerebral cortex observable decades later. Here we tested how developmental and lifespan changes in cortical thickness fit the underlying genetic organizational principles of cortical thickness in a longitudinal sample of 974 participants between 4.1 and 88.5 y of age with a total of 1,633 scans, including 773 scans from children below 12 y. Genetic clustering of cortical thickness was based on an independent dataset of 406 adult twins. Developmental and adult age-related changes in cortical thickness followed closely the genetic organization of the cerebral cortex, with change rates varying as a function of genetic similarity between regions. Cortical regions with overlapping genetic architecture showed correlated developmental and adult age change trajectories and vice versa for regions with low genetic overlap. Thus, effects of genes on regional variations in cortical thickness in middle age can be traced to regional differences in neurodevelopmental change rates and extrapolated to further adult aging-related cortical thinning. This finding suggests that genetic factors contribute to cortical changes through life and calls for a lifespan perspective in research aimed at identifying the genetic and environmental determinants of cortical development and aging.here is a growing realization that events during development impact brain and cognition throughout the entire lifespan (1). For instance, the major portion of the relationship between cortical thickness and IQ in old age can be explained by childhood IQ (2), and genotype may explain a substantial part of the lifetime stability in intelligence (3). Effects of genes on the organization of the cortex have been shown in adults (4-6), but it is unknown whether and how regional differences in cortical development correspond to these regional genetic subdivisions.Although consensus has not been reached for the exact trajectories, cortical thickness as measured by MRI appears to decrease in childhood (7-12). The exact foundation for this thinning is not known, as MRI provides merely representations of the underlying neurobiology, and available histological data cannot with certainty be used to guide interpretations of MRI results. Although speculative, apparent thickness decrease may be grounded in factors such as synaptic pruning and intracortical myelination, although the link between established synaptic processes (13-15) and cortical thickness has not been empirically confirmed. After childhood, cortical thinning continues throughout the remainder of the lifespan, speculated to reflect neuronal shrinkage and reductions in number of spines and synapses (16), although sim...