Structural Brain Architectures Match Intrinsic Functional Networks and Vary across Domains: A Study from 15 000+ Individuals. (3rd June 2020)

• Record Type: Journal Article
• Authors: Luo, Na; Sui, Jing; Abrol, Anees; Chen, Jiayu; Turner, Jessica A; Damaraju, Eswar; Fu, Zening; Fan, Lingzhong; Lin, Dongdong; Zhuo, Chuanjun; Xu, Yong; Glahn, David C; Rodrigue, Amanda L; Banich, Marie T; Pearlson, Godfrey D; Calhoun, Vince D
• Is Part Of: Cerebral cortex. Volume 30:Number 10(2020)
• Page Start: 5460
• Page End: 5470
• Publication Date: 2020-06-03
• Subjects: intrinsic brain networks -- independent component analysis (ICA) -- structure-function coherence -- unimodal cortex -- heteromodal association cortex; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhaa127
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Brain structural networks have been shown to consistently organize in functionally meaningful architectures covering the entire brain. However, to what extent brain structural architectures match the intrinsic functional networks in different functional domains remains under explored. In this study, based on independent component analysis, we revealed 45 pairs of structural-functional (S-F) component maps, distributing across nine functional domains, in both a discovery cohort ( n = 6005) and a replication cohort (UK Biobank, n = 9214), providing a well-match multimodal spatial map template for public use. Further network module analysis suggested that unimodal cortical areas (e.g., somatomotor and visual networks) indicate higher S-F coherence, while heteromodal association cortices, especially the frontoparietal network (FPN), exhibit more S-F divergence. Collectively, these results suggest that the expanding and maturing brain association cortex demonstrates a higher degree of changes compared with unimodal cortex, which may lead to higher interindividual variability and lower S-F coherence.