| Literature DB >> 31276262 |
Jiao Li1,2, Bharat B Biswal1,2,3, Pan Wang1,2, Xujun Duan1,2, Qian Cui4, Huafu Chen1,2, Wei Liao1,2.
Abstract
A major challenge in neuroscience is understanding how brain function emerges from the connectome. Most current methods have focused on quantifying functional connectomes in gray-matter (GM) signals obtained from functional magnetic resonance imaging (fMRI), while signals from white-matter (WM) have generally been excluded as noise. In this study, we derived a functional connectome from WM resting-state blood-oxygen-level-dependent (BOLD)-fMRI signals from a large cohort (n = 488). The WM functional connectome exhibited weak small-world topology and nonrandom modularity. We also found a long-term (i.e., over 10 months) topological reliability, with topological reproducibility within different brain parcellation strategies, spatial distance effect, global and cerebrospinal fluid signals regression or not. Furthermore, the small-worldness was positively correlated with individuals' intelligence values (r = .17, pcorrected = .0009). The current findings offer initial evidence using WM connectome and present additional measures by which to uncover WM functional information in both healthy individuals and in cases of clinical disease.Entities:
Keywords: functional connectome; network topology; resting-state; topological reliability; white matter
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Year: 2019 PMID: 31276262 PMCID: PMC6865787 DOI: 10.1002/hbm.24705
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038