An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization

Abstract

Adolescence is a critical time for the continued maturation of brain networks. Here, we assessed structural connectome development in a large longitudinal sample ranging from childhood to young adulthood. By projecting high-dimensional connectomes into compact manifold spaces, we identified a marked expansion of structural connectomes with the strongest effects in transmodal regions during adolescence. Findings reflected increased within-module connectivity together with increased segregation, indicating increasing differentiation of higher-order association networks from the rest of the brain. Projection of subcortico-cortical connectivity patterns into these manifolds showed parallel alterations in pathways centered on the caudate and thalamus. Connectome findings were contextualized via spatial transcriptome association analysis, highlighting genes enriched in cortex, thalamus, and striatum. Statistical learning of cortical and subcortical manifold features at baseline and their maturational change predicted measures of intelligence at follow-up. Our findings demonstrate that connectome manifold learning can bridge the conceptual and empirical gaps between macroscale network reconfigurations, microscale processes, and cognitive outcomes in adolescent development.

Dissociable Multi-scale Patterns of Development in Personalized Brain Networks

“…Together, these developmental effects served to further distinguish the functional hierarchy that is now well described in adults, and broadly aligns with recent reports using independent methods and datasets (Dong et al, 2020;Nenning et al, 2020). This functional differentiation of cortical hierarchy over development is consistent with evidence that cortical myeloarchitecture further differentiates between unimodal and transmodal regions during adolescence (Paquola et al, 2019), and that transmodal structural networks become increasingly dissimilar from unimodal networks with age (Park et al, 2021). Coupling between hierarchically similar networks may be partially attributable to the propagation of cortical waves along functional hierarchies (Mitra and Raichle, 2016;Matsui et al, 2016;Gu et al, 2021); however, additional research is needed to examine how such waves evolve in development.…”

Schizophrenia polygenic risk during typical development reflects multiscale cortical organization

“…Childhood and adolescent brain development involves dynamic and complex structural changes that are shaped by genetic and environmental factors (Shaw et al, 2006(Shaw et al, , 2007Raznahan et al, 2011;Schmitt et al, 2014;Khundrakpam et al, 2017;Park et al, 2021).…”

“…Childhood and adolescent brain development involves dynamic and complex structural changes that are shaped by genetic and environmental factors (Shaw et al ., 2006, 2007; Raznahan et al ., 2011; Schmitt et al ., 2014; Khundrakpam et al ., 2017; Park et al ., 2021). Longitudinal neuroimaging studies have consistently reported a global increase in cortical volume, thickness, and surface area that typically peaks in late childhood and is followed by decreases in adolescence (Raznahan et al ., 2011; Wierenga et al ., 2014; Tamnes et al ., 2017).…”

Adolescent development of multiscale structural wiring and functional interactions in the human connectome

“…It is controlled by two parameters α and t, where α controls the influence of the density of sampling points on the manifold (α = 0, maximal influence; α = 1, no influence) and t controls the scale of eigenvalues of the diffusion operator. We set α = 0.5 and t = 0 to retain the global relations between data points in the embedded space, following prior applications [17,20,28,41,46,98,99]. Cortical regions with more similar inter-regional patterns are more proximal in this new structural manifold.…”

“…Prior MRI literature has assessed regional changes in brain structure [1][2][3][10][11][12][13][14][15][16], showing age-related widespread decreases in cortical thickness [1,13], as well as increases in intracortical myelin [15][16][17]. Complementing these regional changes, diffusion and functional MRI studies showed an ongoing maturation of both the microstructure of inter-connecting white matter tracts as well as large-scale developmental changes in functional network organization, indicative of shifts in brain connectivity towards a more distributed topology [18][19][20]. Utilizing multimodal longitudinal MRI analyses, here, we explored how adolescent structural network development gives rise to potential shifts in functional network architecture.…”