The neurobiology of childhood structural brain development: conception through adulthood

Abstract

The study of the function and structure of the human brain dates back centuries, when philosophers and physicians theorized about the localization of specific cognitive functions and the structure and organization of underlying brain tissue. In more recent years, the advent of non-invasive techniques such as Magnetic Resonance Imaging (MRI) has allowed scientists unprecedented opportunities to further our understanding not only of structure and function, but of trajectories of brain development in typical and a-typical child and adult populations. In this chapter, we hope to provide a system-level approach to introduce what we have learned about structural brain development from conception through adulthood. We discuss important findings from MRI studies, and the directions that future imaging studies can take in the concerted effort to enhance our understanding of brain development, and thus to enhance our ability to develop interventions for various neurodevelopmental disorders.

Fig. 1

Cortical thickness shows regional and temporal specificity with development (Sowell et al. 2003). Shown is a surface rendering of the left hemisphere of the brain (anterior to posterior is left to right), with scatterplots of nonlinear relationship between gray matter density and age in years. Graphs are placed over the corresponding brain regions. All axes are identical; gray matter density is plotted on the x-axis, and age in years (range: 7–87 years) is plotted on the y-axis. Prefrontal and parietal regions show steeper or prolonged rates of decline compared to phylogenetically older regions like the occipital lobe. In contrast, temporal regions show increases in gray matter density before starting to decline in adolescence

Fig. 2

Localized thickness maps of both cerebral hemispheres reveal Pearson’s correlations (p ≤ 0.05) between changes in gray matter thickness and behavioral scores on a phonological processing, and b fine motor skill in children (ages 5–11 years). A double dissociation is seen between thickness and behavior, as white areas represent positive relationships between behavior and thickness change; red areas represent negative correlations (used with permission; Lu et al. 2007)

Fig. 3

Graphs and cortical renderings depicting the complexity of cortical thickness development in a sample of 375 children, adolescents, and adults (aged 3.5–33 years) (used with permission; Shaw et al. 2008). Graphs depict the patterns of growth for their corresponding column. The brain maps show the vertices having a cubic (red), quadratic (green), or linear (blue) developmental trajectory. Vertical brain maps represent dorsal, right lateral, left lateral, left medial, and right medial views, respectively. The corpus callosum and subcortical regions are blacked out

Fig. 4

Linear and nonlinear development of orbitofrontal cortical thickness (used with permission; Shaw et al. 2008). a 3-Dimensional rendering of the anterior view of the brain with colors representing the different growth trajectories seen in the orbitofrontal cortex. Anterior and lateral orbitofrontal regions have a cubic fit (red); medial and posterior orbitofrontal regions demonstrate a quadratic fit (green) and linear (blue) trajectories. b Growth trajectories are superimposed on a cytoarchitectonic map, highlighting that the different growth trajectories correspond to underlying neural architecture. Cubic functions (red) are largely seen in regions where homotypical cortical layers (six-layers) are present, whereas regions of the orbitofrontal cortex with fewer and less organized layers tend to have quadratic or linear regions (green and blue). c Agraphical depiction of the different type of growth trajectories seen in the orbitofrontal cortex