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Brain hubs in lesion models: Predicting functional network topology with lesion patterns in patients.


ABSTRACT: Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages. Patients' cortical lesion distribution patterns could significantly predict the functional network topology and a set of regions with significant weights in the prediction models were identified as "lesion hubs". Intriguingly, we found two different types of lesion hubs, whose lesions associated with changes of network topology towards relatively different directions, being either more integrated (global) or more segregated (local), and correspond to hubs identified in healthy functional network in complex manners. Our results pose further important questions about the potential dynamics of the functional brain network after brain damage.

SUBMITTER: Yuan B 

PROVIDER: S-EPMC5738424 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Brain hubs in lesion models: Predicting functional network topology with lesion patterns in patients.

Yuan Binke B   Fang Yuxing Y   Han Zaizhu Z   Song Luping L   He Yong Y   Bi Yanchao Y  

Scientific reports 20171220 1


Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages. Patients' cortical lesion distribution patterns could significantl  ...[more]

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