| Literature DB >> 32488253 |
Na Luo1,2, Jing Sui1,2,3, Anees Abrol4, Jiayu Chen4, Jessica A Turner5, Eswar Damaraju4, Zening Fu4, Lingzhong Fan1,2, Dongdong Lin4, Chuanjun Zhuo6, Yong Xu7, David C Glahn8, Amanda L Rodrigue8, Marie T Banich9,10, Godfrey D Pearlson11,12,13, Vince D Calhoun4,14,15.
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.Entities:
Keywords: heteromodal association cortex; independent component analysis (ICA); intrinsic brain networks; structure-function coherence; unimodal cortex
Mesh:
Year: 2020 PMID: 32488253 PMCID: PMC7566687 DOI: 10.1093/cercor/bhaa127
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357