TY - GEN
T1 - EEG-based brain network analysis in stroke patients during a motor execution task
AU - Zhao, Chunli
AU - Li, Rihui
AU - Wang, Chushan
AU - Huang, Weitian
AU - Zhang, Yingchun
N1 - Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/5/16
Y1 - 2019/5/16
N2 - Post-stroke survivors often suffer motor function disorders, which are usually associated with anatomical and functional alterations of brain network. Previous EEG-based brain network analyses mainly focused on stroke-linked brain network in resting state and single aspect (globally or regionally), leaving the pattern of functional connectivity (FC) in stroke patients during specific motion task uncovered yet. In this study, we investigated stroke specific FC patterns in patients who suffered unilateral hemispheric stroke during a motor execution task. Partial correlation coefficients between multiple electroencephalography (EEG) channels were computed to construct the functional networks for healthy controls and stroke patients. The graph-based analysis was then performed to characterize specific FC patterns in stroke patients. Results suggested that brain networks were characterized in stroke patients by lower global efficiency and clustering coefficient in alpha and beta band, compared to healthy controls. Regionally, stroke patients exhibited weaker local connection in motor area of affected hemisphere during motor execution, which may explain their motor deficits. The findings of our study may offer new insight to study the neural plasticity and brain reorganization after stroke.
AB - Post-stroke survivors often suffer motor function disorders, which are usually associated with anatomical and functional alterations of brain network. Previous EEG-based brain network analyses mainly focused on stroke-linked brain network in resting state and single aspect (globally or regionally), leaving the pattern of functional connectivity (FC) in stroke patients during specific motion task uncovered yet. In this study, we investigated stroke specific FC patterns in patients who suffered unilateral hemispheric stroke during a motor execution task. Partial correlation coefficients between multiple electroencephalography (EEG) channels were computed to construct the functional networks for healthy controls and stroke patients. The graph-based analysis was then performed to characterize specific FC patterns in stroke patients. Results suggested that brain networks were characterized in stroke patients by lower global efficiency and clustering coefficient in alpha and beta band, compared to healthy controls. Regionally, stroke patients exhibited weaker local connection in motor area of affected hemisphere during motor execution, which may explain their motor deficits. The findings of our study may offer new insight to study the neural plasticity and brain reorganization after stroke.
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U2 - 10.1109/NER.2019.8716954
DO - 10.1109/NER.2019.8716954
M3 - Conference contribution
AN - SCOPUS:85066762908
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 887
EP - 890
BT - 9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Y2 - 20 March 2019 through 23 March 2019
ER -