Abstract
The coupling strength between electroencephalogram (EEG) and electromyography (EMG) signals during motion control reflects the interaction between the cerebral motor cortex and muscles. Therefore, neuromuscular coupling characterization is instructive in assessing motor function. In this study, to overcome the limitation of losing the characteristics of signals in conventional time series symbolization methods, a variable scale symbolic transfer entropy (VS-STE) analysis approach was proposed for corticomuscular coupling evaluation. Post-stroke patients (n = 5) and healthy volunteers (n = 7) were recruited and participated in various tasks (left and right hand gripping, elbow bending). The proposed VS-STE was employed to evaluate the corticomuscular coupling strength between the EEG signal measured from the motor cortex and EMG signal measured from the upper limb in both the time-domain and frequency-domain. Results showed a greater strength of the bi-directional (EEG-to-EMG and EMG-to-EEG) VS-STE in post-stroke patients compared to healthy controls. In addition, the strongest EEG–EMG coupling strength was observed in the beta frequency band (15–35 Hz) during the upper limb movement. The predefined coupling strength of EMG-to-EEG in the affected side of the patient was larger than that of EEG-to-EMG. In conclusion, the results suggested that the corticomuscular coupling is bi-directional, and the proposed VS-STE can be used to quantitatively characterize the non-linear synchronization characteristics and information interaction between the primary motor cortex and muscles.
Highlights
Electroencephalogram (EEG) is a non-invasive brain imaging technique that uses scalp electrodes to measure the voltage fluctuations induced by the mass electrical activity of neurons [1]
EEG signals from C3/C4 channel located in the primary motor zone, CP5/CP6 channel in the primary somatic sensory area, and EMG signals from the flexor digitorum superficialis (FDS), the bicipital muscle (MBB) channel were selected to study the transfer entropy (TE) in the article
It can be observed that delays of the descending (EEG to EMG) and ascending (EMG to EEG) pathways are different for individual subject, but generally concentrated around 20–30 ms, which is consistent with the results of a previous study [24]
Summary
Electroencephalogram (EEG) is a non-invasive brain imaging technique that uses scalp electrodes to measure the voltage fluctuations induced by the mass electrical activity of neurons [1]. The STE has been used to analyze the non-linear functional connection between EEG single and surface EMG signals of hand muscles [16], which demonstrated that the functional corticomuscular coupling is significant in the beta band in the static force output for healthy subjects. The STE has only been applied to health subjects so far, has not been tested in stroke patient population yet [16,17,18] To bridge this gap, a variable scale symbolic transfer entropy (VS-STE) analysis approach was developed in this study to better investigate the corticomuscular coupling in both post-stroke patients and healthy volunteers. The EEG–EMG coupling strength of subjects were quantitatively evaluated in terms of significant area, which provided evidence to apply corticomuscular coupling in the rehabilitative evaluation of motor function disorders
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