Dynamic modulation of corticomuscular coherence during ankle dorsiflexion after stroke: towards hybrid BCI for lower-limb rehabilitation

<i>Objective</i>. Hybrid brain-computer interface (BCI) systems incorporate electroencephalography (EEG) and electromyography (EMG) signals to extract corticomuscular coherence (CMC) features, enabling self-modulation of neural communication. While promising for stroke rehabilitation, the neurophysiological mechanism underlying hybrid BCI therapy remains poorly understood. To address this gap, we characterized post-stroke CMC dynamics during ankle dorsiflexion and further established their relationship with functional motor recovery.<i>Approach</i>. We acquired synchronous EEG and high-density EMG recordings from 13 subacute stroke patients (with their affected limb) before and after three-week rehabilitation, and 9 age-matched healthy controls (using their dominant limb) during isometric ankle dorsiflexion. Using multivariate coupling analysis, we computed EEG and EMG projection vectors to identify optimal coupling patterns. Subsequently, we derived CMC spectra and topographies through coherence analysis to characterize corticomuscular interactions at spatial and spectral scales.<i>Main results</i>. Compared to healthy controls, stroke patients demonstrated reduced beta-band CMC patterns, particularly within the sensorimotor areas involved in the foot movement. No significant differences in CMC patterns were observed between stroke patients before and after rehabilitation training. Further analysis revealed significant correlation between beta-band CMC changes and clinical improvements measured by the Berg balance scale.<i>Significance</i>. Beta-band CMC is a potential neurophysiological biomarker of motor recovery following stroke. These findings provide novel insights into the disrupted corticomuscular communication underlying post-stroke motor dysfunction, while offering mechanistic evidence to guide the design and implementation of hybrid BCI systems that target these specific biomarkers for therapeutic intervention.