EEG-based predictors of motor recovery during immersive VR-BCI rehabilitation

Motor impairment following stroke frequently leads to long-term disability, limiting independence and quality of life. Brain-Computer Interface (BCI) systems integrating motor imagery (MI) with virtual reality (VR) offer promising avenues for enhancing neuroplasticity and engagement through immersive, real-time, and proprioceptive feedback. Yet, identifying reliable electroencephalography (EEG)-based biomarkers that reflect or predict recovery remains challenging. This study investigated the relationship between event-related desynchronization (ERD) dynamics during MI-VR training and motor recovery in individuals with chronic stroke. Fourteen participants with stroke (9 experimental, 5 control) completed a 4-week VR-BCI intervention and were compared with a non-stroke reference cohort (N = 35). Linear mixed-effects models assessed ERD modulation across sessions and groups, and a two-stage regression evaluated the predictive value of ERD features for Fugl-Meyer Assessment (FMA) gains. Results showed no significant ERD change across sessions, but stroke participants exhibited significantly reduced ERD compared to controls. Baseline ERD amplitude predicted motor improvement, whereas ERD progression did not. Ipsilateral ERD showed a compensatory trend in ischemic stroke. These findings indicate that baseline ERD may serve as a stronger prognostic biomarker than short-term ERD dynamics, supporting the development of personalized VR-BCI rehabilitation strategies for chronic stroke recovery.