A study of cortical activation and corticomuscular coupling enhancement following pre-task electrical stimulation in...

Objective. Motor imagery (MI)-based brain-computer interfaces have been extensively studied. However, their widespread application is limited by the difficulty in extracting motor intentions from electroencephalography (EEG) signals, leading to low recognition rates. Additionally, the phenomenon of MI blindness in some individuals further limits its applicability. Previous studies have attempted to improve MI ability through electrical stimulation (ES). However, applying ES during MI may introduce EEG artifacts and interfere with participants' concentration. The goal of this study is to investigate a new experimental paradigm. The new experimental paradigm improves MI ability through pre-task ES while preventing participant distraction or EEG artifacts.Approach. This study implemented two paradigms: MI with pre-task ES and MI-only. Electrical stimulation was applied over hand muscle groups. Electromyography (EMG) and 64-channel EEG signals were simultaneously recorded under two experimental conditions.Main results. We analyzed cortical activities and correlations between different brain regions under the two experimental conditions. Participants in the MI-ES condition exhibited a higher level of brain activation compared to the MI-Only condition. Additionally, in the MI-ES condition, the correlation between participants' EEG and EMG signals increased after ES, indicating that the activation level of the motor-related cortex increased. A novel convolutional spiking neural network was applied to classify motor intentions, with participants achieving higher accuracy under the MI-ES condition, demonstrating enhanced MI ability through pre-task ES.Significance. This research demonstrates that pre-task ES significantly enhances MI ability, while also increasing cortical activation and corticomuscular coupling without introducing EEG artifacts or attentional interference.