Synchronization lag in post stroke: relation to motor function and structural connectivity
Author(s) -
Xin Wang,
Caio Seguin,
Andrew Zalesky,
Wan-wa Wong,
ChiuWing Winnie Chu,
K.Y. Tong
Publication year - 2019
Publication title -
network neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.128
H-Index - 18
ISSN - 2472-1751
DOI - 10.1162/netn_a_00105
Subject(s) - lag , synchronization (alternating current) , connectome , resting state fmri , phase lag , neuroscience , functional connectivity , granger causality , computer science , psychology , mathematics , machine learning , telecommunications , computer network , channel (broadcasting)
Stroke is characterized by delays in the resting-state hemodynamic response, resulting in synchronization lag in neural activity between brain regions. However, the structural basis of this lag remains unclear. In this study, we used resting-state functional MRI (rs-fMRI) to characterize synchronization lag profiles between homotopic regions in 15 individuals (14 males, 1 female) with brain lesions consequent to stroke as well as a group of healthy comparison individuals. We tested whether the network communication efficiency of each individual's structural brain network (connectome) could explain interindividual and interregional variation in synchronization lag profiles. To this end, connectomes were mapped using diffusion MRI data, and communication measures were evaluated under two schemes: shortest paths and navigation. We found that interindividual variation in synchronization lags was inversely associated with communication efficiency under both schemes. Interregional variation in lag was related to navigation efficiency and navigation distance, reflecting its dependence on both distance and structural constraints. Moreover, severity of motor deficits significantly correlated with average synchronization lag in stroke. Our results provide a structural basis for the delay of information transfer between homotopic regions inferred from rs-fMRI and provide insight into the clinical significance of structural-functional relationships in stroke individuals.
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