Electroencephalogram-Electromyography Coupling Analysis in Stroke Based on Symbolic Transfer Entropy.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Science

Background:

• Neuromuscular coupling, the interaction between the brain's motor cortex and muscles, is crucial for motor control.
• Assessing this coupling aids in understanding motor function and neurological conditions like stroke.
• Conventional methods for analyzing time-series signals can lose important signal characteristics.

Purpose of the Study:

• To introduce a novel analysis approach, variable scale symbolic transfer entropy (VS-STE), for evaluating corticomuscular coupling.
• To overcome limitations of conventional methods in preserving signal characteristics during analysis.
• To quantitatively assess corticomuscular coupling strength in post-stroke patients and healthy controls.

Main Methods:

• Recruited post-stroke patients (n=5) and healthy volunteers (n=7) for motor tasks (hand gripping, elbow bending).
• Measured electroencephalogram (EEG) from the motor cortex and electromyography (EMG) from the upper limb.
• Applied the proposed VS-STE method to analyze time- and frequency-domain corticomuscular coupling.

Main Results:

• Post-stroke patients showed significantly higher bi-directional VS-STE (EEG-to-EMG and EMG-to-EEG) compared to healthy controls.
• The strongest corticomuscular coupling occurred in the beta frequency band (15-35 Hz) during upper limb movement.
• In affected limbs of patients, EMG-to-EEG coupling strength exceeded EEG-to-EMG coupling.

Conclusions:

• Corticomuscular coupling is a bi-directional process.
• The VS-STE method effectively quantifies non-linear synchronization and information exchange between the motor cortex and muscles.
• Findings highlight potential for VS-STE in assessing motor function and neurological impairments.