Within and between electrophysiology networks for EEG and EMG under different thumb forces

Compared to the research on the single central or peripheral nervous system, there is still a lack of systematic information on the relationship between the two. It is necessary to clarify whether there is information interaction between the central nervous system and the peripheral motor system via brain-muscle coupling. In this study, we constructed the coherence networks within and between the brain and muscles at different levels of thumb force. We then developed a model that can accurately identify different levels of thumb force based on their distinct network features. In the internal coherence network of EEG or EMG, high-level force activity evokes stronger and more concentrated network patterns than low-level force activity. In the corticomuscular coherence network (CMCN) between EEG and EMG, there is a stronger coupling relationship between non-contralateral motor brain regions and most muscle groups for high-level force compared to low-level force. The CMCN features led to significant improvements in identifying different thumb forces, resulting in an accuracy rate of 99.00 %, which is at least 4.00 % higher than using EEG or EMG alone. This study indicates that there is information interaction between the central nervous system and the peripheral motor system during movement, which can have important implications for improving rehabilitation and motor control methods.