TY - GEN
T1 - Brain Network Analysis of Hand Motor Execution and Imagery Based on Conditional Granger Causality
AU - He, Yuqing
AU - Hao, Bin
AU - Belkacem, Abdelkader Nasreddine
AU - Zhang, Jiaxin
AU - Li, Penghai
AU - Liang, Jun
AU - Wang, Changming
AU - Chen, Chao
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - The exploration of neural activity patterns in motor imagery offers a new way of thinking for improving motor skills in normal individuals and for rehabilitating patients with motor disorders. In this paper, the influence relationship between the brain network of the brain motor system and the relevant motor intervals was investigated by collecting EEG signals during finger motor execution and motor imagery from 11 subjects. To address the problem that Granger causality can only reflect the interaction between two temporal variables, a conditional Granger causality analysis was introduced to analysis the brain network relationships between multiple motor compartments. The results showed that the brain network map of finger motor execution had more effective connections than that of finger motor imagination, and it was found that there were effective connection loops between left PMA and left MA, left MA and left SA, and left SA and right SA for both finger motor execution and motor imagination, and the most important connection in motor function was from premotor area to primary motor area.
AB - The exploration of neural activity patterns in motor imagery offers a new way of thinking for improving motor skills in normal individuals and for rehabilitating patients with motor disorders. In this paper, the influence relationship between the brain network of the brain motor system and the relevant motor intervals was investigated by collecting EEG signals during finger motor execution and motor imagery from 11 subjects. To address the problem that Granger causality can only reflect the interaction between two temporal variables, a conditional Granger causality analysis was introduced to analysis the brain network relationships between multiple motor compartments. The results showed that the brain network map of finger motor execution had more effective connections than that of finger motor imagination, and it was found that there were effective connection loops between left PMA and left MA, left MA and left SA, and left SA and right SA for both finger motor execution and motor imagination, and the most important connection in motor function was from premotor area to primary motor area.
KW - Brain network
KW - Conditional granger causality analysis
KW - EEG signal
KW - Motor execution
KW - Motor imagery
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U2 - 10.1007/978-981-19-8222-4_11
DO - 10.1007/978-981-19-8222-4_11
M3 - Conference contribution
AN - SCOPUS:85144206171
SN - 9789811982217
T3 - Communications in Computer and Information Science
SP - 125
EP - 134
BT - Human Brain and Artificial Intelligence - Third International Workshop, HBAI 2022, Held in Conjunction with IJCAI-ECAI 2022, Revised Selected Papers
A2 - Ying, Xiaomin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Workshop on Human Brain and Artificial Intelligence, HBAI 2022, held in conjunction with 31st International Joint Conference on Artificial Intelligence and 23rd European Conference on Artificial Intelligence, IJCAI-ECAI 2022
Y2 - 23 July 2022 through 23 July 2022
ER -