Modular Development of Cortical Gray Matter Across Childhood and Adolescence

Abstract

Brain maturation across childhood and adolescence is characterized by cortical thickness (CT) and volume contraction, and early expansion of surface area (SA). These processes occur asynchronously across the cortical surface, with functional, topographic, and network-based organizing principles proposed to account for developmental patterns. Characterizing regions undergoing synchronized development can help determine whether "maturational networks" overlap with well-described functional networks, and whether they are targeted by neurodevelopmental and psychiatric disorders. In the present study, we modeled changes with age in CT, SA, and volume from 335 typically developing subjects in the NIH MRI study of normal brain development, with 262 followed longitudinally for a total of 724 scans. Vertices showing similar maturation between 5 and 22 years were grouped together using data-driven clustering. Patterns of CT development distinguished sensory and motor regions from association regions, and were vastly different from SA patterns, which separated anterior from posterior regions. Developmental modules showed little similarity to networks derived from resting-state functional connectivity. Our findings present a novel perspective on maturational changes across the cortex, showing that several proposed organizing principles of cortical development co-exist, albeit in different structural parameters, and enable visualization of developmental trends occurring in parallel at remote cortical sites.

Age‐associated patterns in gray matter volume, cerebral perfusion and BOLD oscillations in children and adolescents

“…This work is exciting in that it may identify networks of regions that are targeted by specific brain disorders [Alexander-Bloch et al, 2014;Douaud et al, 2014;]. This is consistent with two recent studies from our group, using different methods applied to a separate dataset Krongold et al, 2015], and with early descriptions of cortical developmental patterns which showed a more protracted trajectory for prefrontal regions [Gogtay et al, 2004]. This is consistent with two recent studies from our group, using different methods applied to a separate dataset Krongold et al, 2015], and with early descriptions of cortical developmental patterns which showed a more protracted trajectory for prefrontal regions [Gogtay et al, 2004].…”

“…We hypothesized that changes in GMV would show a developmental pattern that divides anterior from posterior brain regions, consistent with our previous work Krongold et al, 2015]. We further hypothesized that similar patterns would be apparent in CBF and fALFF measures, as CBF has similarly been shown to globally decline with age following a peak in early childhood Biagi et al, 2007;Chiron et al, 1992;Wang and Licht, 2006;Wintermark et al, 2004], that parallels what is seen in global GMV.…”

“…Associations between structural and functional development have been proposed to occur at the network level: that is, it has been shown that regions which are part of common functional networks mature at similar rates [Raznahan et al, 2011]. However, data-driven approaches to identify structural maturational networks have tended to identify a set of networks in gray and white matter development that do not easily map onto canonical resting-state networks [Alexander-Bloch et al, 2014;Bray et al, 2015;Krongold et al, 2015]. It therefore remains an open question how anatomical changes such as gray matter thinning relate to developmental changes in functional networks and responses.…”

“…These developmental processes unfold at different rates across the brain [Gogtay et al, 2004;Lebel et al, 2008]. Understanding patterns in development is of interest, both to fully characterize typical development and to determine whether brain disorders target "maturational networks" [Alexander-Bloch et al, 2014, 2013Bray et al, 2015Krongold et al, 2015. Associations between structural and functional development have been proposed to occur at the network level: that is, it has been shown that regions which are part of common functional networks mature at similar rates [Raznahan et al, 2011].…”

Gray matter network differences between behavioral variant frontotemporal dementia and Alzheimer's disease

“…This method provides a precise quantitative description of cortical structure by representing brain morphology as a network in which each cortical area represents a node and nodes are connected by edges when they show as statistical covariance in their morphometric features (local thickness and folding structure of the cortex). Patterns of coordinated grey matter morphology have been proposed to reflect functional co-activation (Alexander-Bloch et al, 2013;Andrews et al, 1997;Bailey et al, 2014;Hopkins, 2004;Krongold et al, 2015), axonal connectivity (Budday et al, 2014;Gong et al, 2012) and/or genetic factors (Chen et al, 2013;Schmitt et al, 2009;2008). Analogously, brain areas that are involved in specific cognitive or behavioral functions seem to deteriorate in a coordinated way (Sepulcre et al, 2012;Voss and Zatorre, 2015).…”