Global synchronization of functional corticomuscular coupling under precise grip tasks using multichannel EEG and EMG signals

• Published in: Cognitive neurodynamics Vol. 18; no. 6; pp. 3727 - 3740
• Main Authors: Chen, Xiaoling, Shen, Tingting, Hao, Yingying, Zhang, Jinyuan, Xie, Ping
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2024; Springer Nature B.V
• Subjects: Artificial Intelligence; Biochemistry; Biomedical and Life Sciences; Biomedicine; Brain; Brain mapping; Cognitive Psychology; Computer Science; Cortex (motor); Coupling; EEG; Electroencephalography; Electromyography; Experiments; Mapping; Motor task performance; Muscles; Neurosciences; Research Article; Synchronism; Synchronization; Weight; Functional corticomuscular coupling; Multichannel EEG multivariate; Global synchronization index; Precise grip
• ISSN: 1871-4080; 1871-4099
• DOI: 10.1007/s11571-024-10157-2

Functional corticomuscular coupling (FCMC), a phenomenon describing the information interaction between the cortex and muscles, plays an important role in assessing hand movements. However, related studies mainly focused on specific actions by one-to-one mapping between the brain and muscles, ignoring the global synchronization across the motor system. Little research has been done on the FCMC difference between the brain and different muscle groups in terms of precise grip tasks. This study combined the maximum information coefficient (MIC) and the S estimation method and constructed a multivariate global synchronization index (MGSI) to measure the FCMC by analyzing the multichannel electroencephalogram (EEG) and electromyogram (EMG) during precise grip tasks. Both signals were collected from 12 healthy subjects while performing different weight object tasks. Our results on Hilbert-Huang spectral entropy (HHSE) of signals showed differences in task stages in both β (13–30 Hz) and γ (31–45 Hz) bands. The weight difference was reflected in the HHSE of channel CP5 and muscles at both ends of the upper limb. The one-to-one mapping with MIC between EEG and the muscle pair AD-FDI showed larger MIC values than the muscle pair B-CED; the same trend was seen on the MGSI values. However, the difference in weight of static tasks was not significant. Both MGSI values and the connect ratio of EEG were related to HHSE values. This work investigated the changes in the cortex and muscles during precise grip tasks from different perspectives, contributing to a better understanding of human motor control.