4.6 Article

Functional alteration due to structural damage is network dependent: insight from multiple sclerosis

期刊

CEREBRAL CORTEX
卷 33, 期 10, 页码 6090-6102

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhac486

关键词

functional connectivity; structural connectivity; connectome; multiple sclerosis; resting-state network

向作者/读者索取更多资源

This study investigated how the brain's functional organization changes over time with regard to structural damage, using multiple sclerosis as a model. It found that higher-order networks are more likely to experience changes in functional connectivity in response to structural damage compared to lower-order sensory networks.
Little is known about how the brain's functional organization changes over time with respect to structural damage. Using multiple sclerosis as a model of structural damage, we assessed how much functional connectivity (FC) changed within and between preselected resting-state networks (RSNs) in 122 subjects (72 with multiple sclerosis and 50 healthy controls). We acquired the structural, diffusion, and functional MRI to compute functional connectomes and structural disconnectivity profiles. Change in FC was calculated by comparing each multiple sclerosis participant's pairwise FC to controls, while structural disruption (SD) was computed from abnormalities in diffusion MRI via the Network Modification tool. We used an ordinary least squares regression to predict the change in FC from SD for 9 common RSNs. We found clear differences in how RSNs functionally respond to structural damage, namely that higher-order networks were more likely to experience changes in FC in response to structural damage (default mode R-2 = 0.160-0.207, P < 0.001) than lower-order sensory networks (visual network 1 R-2 = 0.001-0.007, P = 0.157-0.387). Our findings suggest that functional adaptability to structural damage depends on how involved the affected network is in higher-order processing.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据