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Brain development is characterized by an increase in structural and functional segregation, which supports the specialization of cognitive processes within the context of network neuroscience. In this study, we investigated age-related changes in morphological segregation using individual Regional Radiomics Similarity Networks (R2SNs) constructed with a longitudinal dataset of 494 T1-weighted MR scans from 309 typically developing children aged 6.2 to 13 years at baseline. Segertation indices were defined as the relative difference in connectivity strengths within and between modules and cacluated at the global, system and local levels. Linear mixed-effect models revealed longitudinal increases in both global and system segregation indices, particularly within the limbic and dorsal attention network, and decreases within the ventral attention network. Superior performance in working memory and inhibitory control was associated with higher system-level segregation indices in default, frontoparietal, ventral attention, somatomotor and subcortical systems, and lower local segregation indices in visual network regions, regardless of age. Furthermore, gene enrichment analysis revealed correlations between age-related changes in local segregation indices and regional expression levels of genes related to developmental processes. These findings provide novel insights into typical brain developmental changes using R2SN-derived segregation indices, offering a valuable tool for understanding human brain structural and cognitive maturation.

Abstract Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.