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G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery

Motor imagery is one of the classical paradigms which have been used in brain-computer interface and motor function recovery. Finger movement-based motor execution is a complex biomechanical architecture and a crucial task for establishing most complicated and natural activities in daily life. Some...

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Autores principales: Chen, Chao, Zhang, Jiaxin, Belkacem, Abdelkader Nasreddine, Zhang, Shanting, Xu, Rui, Hao, Bin, Gao, Qiang, Shin, Duk, Wang, Changming, Ming, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6791225/
https://www.ncbi.nlm.nih.gov/pubmed/31662834
http://dx.doi.org/10.1155/2019/5068283
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author Chen, Chao
Zhang, Jiaxin
Belkacem, Abdelkader Nasreddine
Zhang, Shanting
Xu, Rui
Hao, Bin
Gao, Qiang
Shin, Duk
Wang, Changming
Ming, Dong
author_facet Chen, Chao
Zhang, Jiaxin
Belkacem, Abdelkader Nasreddine
Zhang, Shanting
Xu, Rui
Hao, Bin
Gao, Qiang
Shin, Duk
Wang, Changming
Ming, Dong
author_sort Chen, Chao
collection PubMed
description Motor imagery is one of the classical paradigms which have been used in brain-computer interface and motor function recovery. Finger movement-based motor execution is a complex biomechanical architecture and a crucial task for establishing most complicated and natural activities in daily life. Some patients may suffer from alternating hemiplegia after brain stroke and lose their ability of motor execution. Fortunately, the ability of motor imagery might be preserved independently and worked as a backdoor for motor function recovery. The efficacy of motor imagery for achieving significant recovery for the motor cortex after brain stroke is still an open question. In this study, we designed a new paradigm to investigate the neural mechanism of thirty finger movements in two scenarios: motor execution and motor imagery. Eleven healthy participants performed or imagined thirty hand gestures twice based on left and right finger movements. The electroencephalogram (EEG) signal for each subject during sixty trials left and right finger motor execution and imagery were recorded during our proposed experimental paradigm. The Granger causality (G-causality) analysis method was employed to analyze the brain connectivity and its strength between contralateral premotor, motor, and sensorimotor areas. Highest numbers for G-causality trials of 37 ± 7.3, 35.5 ± 8.8, 36.3 ± 10.3, and 39.2 ± 9.0 and lowest Granger causality coefficients of 9.1 ± 3.2, 10.9 ± 3.7, 13.2 ± 0.6, and 13.4 ± 0.6 were achieved from the premotor to motor area during execution/imagination tasks of right and left finger movements, respectively. These results provided a new insight into motor execution and motor imagery based on hand gestures, which might be useful to build a new biomarker of finger motor recovery for partially or even completely plegic patients. Furthermore, a significant difference of the G-causality trial number was observed during left finger execution/imagery and right finger imagery, but it was not observed during the right finger execution phase. Significant difference of the G-causality coefficient was observed during left finger execution and imagery, but it was not observed during right finger execution and imagery phases. These results suggested that different MI-based brain motor function recovery strategies should be taken for right-hand and left-hand patients after brain stroke.
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spelling pubmed-67912252019-10-29 G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery Chen, Chao Zhang, Jiaxin Belkacem, Abdelkader Nasreddine Zhang, Shanting Xu, Rui Hao, Bin Gao, Qiang Shin, Duk Wang, Changming Ming, Dong J Healthc Eng Research Article Motor imagery is one of the classical paradigms which have been used in brain-computer interface and motor function recovery. Finger movement-based motor execution is a complex biomechanical architecture and a crucial task for establishing most complicated and natural activities in daily life. Some patients may suffer from alternating hemiplegia after brain stroke and lose their ability of motor execution. Fortunately, the ability of motor imagery might be preserved independently and worked as a backdoor for motor function recovery. The efficacy of motor imagery for achieving significant recovery for the motor cortex after brain stroke is still an open question. In this study, we designed a new paradigm to investigate the neural mechanism of thirty finger movements in two scenarios: motor execution and motor imagery. Eleven healthy participants performed or imagined thirty hand gestures twice based on left and right finger movements. The electroencephalogram (EEG) signal for each subject during sixty trials left and right finger motor execution and imagery were recorded during our proposed experimental paradigm. The Granger causality (G-causality) analysis method was employed to analyze the brain connectivity and its strength between contralateral premotor, motor, and sensorimotor areas. Highest numbers for G-causality trials of 37 ± 7.3, 35.5 ± 8.8, 36.3 ± 10.3, and 39.2 ± 9.0 and lowest Granger causality coefficients of 9.1 ± 3.2, 10.9 ± 3.7, 13.2 ± 0.6, and 13.4 ± 0.6 were achieved from the premotor to motor area during execution/imagination tasks of right and left finger movements, respectively. These results provided a new insight into motor execution and motor imagery based on hand gestures, which might be useful to build a new biomarker of finger motor recovery for partially or even completely plegic patients. Furthermore, a significant difference of the G-causality trial number was observed during left finger execution/imagery and right finger imagery, but it was not observed during the right finger execution phase. Significant difference of the G-causality coefficient was observed during left finger execution and imagery, but it was not observed during right finger execution and imagery phases. These results suggested that different MI-based brain motor function recovery strategies should be taken for right-hand and left-hand patients after brain stroke. Hindawi 2019-10-02 /pmc/articles/PMC6791225/ /pubmed/31662834 http://dx.doi.org/10.1155/2019/5068283 Text en Copyright © 2019 Chao Chen et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Chao
Zhang, Jiaxin
Belkacem, Abdelkader Nasreddine
Zhang, Shanting
Xu, Rui
Hao, Bin
Gao, Qiang
Shin, Duk
Wang, Changming
Ming, Dong
G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery
title G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery
title_full G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery
title_fullStr G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery
title_full_unstemmed G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery
title_short G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery
title_sort g-causality brain connectivity differences of finger movements between motor execution and motor imagery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6791225/
https://www.ncbi.nlm.nih.gov/pubmed/31662834
http://dx.doi.org/10.1155/2019/5068283
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