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Huimin Huang

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Open access Aug 2026

ERD Full-process Longitudinal Trend and Pre-post Motor Recovery Under BCI-controlled Sixth-finger Neurofeedback Intervention in Stroke Patients: an Exploratory Single-arm Study.

Motor imagery-based brain-computer interface (MI-BCI) is used in stroke rehabilitation to match brain activity with contingent feedback to establish closed-loop pathways and provide a measure of neuroplasticity changes in patients. However, most studies assessed neural function only at pre- and post-train, thereby longitudinal trends of neural patterns and mechanisms during full-process of intervention remain unclear. Fourteen stroke patients were recruited to receive a total of 8-session (2-week) MI-BCI-controlled "sixth-finger" intervention. Resting-state electroencephalography (EEG) and clinical scales, including the Fugl-Meyer Assessment (FMA-UE) and Barthel Index (BI), were evaluated pre- and post-train. Furthermore, MI tasks EEG signals throughout the full-process of intervention were tracked to reflect the longitudinal continuous trends of neural activity. EEG longitudinal trend shows two phases over full-process of intervention: event-related desynchronization (ERD) gradually increased in the first week of training, weakened and focused on the contralateral sensorimotor area in the second week, and showed a significant correlation over sessions. And resting-state functional connectivity increased after intervention. Motor function improved significantly from pre- to post-train by clinical metrics, with + 7.9 in FMA-UE and + 7.1 in BI. More than half of patients (9/14) reached the minimally clinically important difference (MCID) of 6.6 points change for FMA-UE after therapy. Meanwhile, the improvement of motor function is associated with the enhancement of resting-state functional connectivity. This work reveals longitudinal trend of neural patterns over full-process of intervention and its correlation with motor recovery, providing crucial evidence for understanding the mechanisms of neuroplasticity in stroke rehabilitation.

Zhuang Wang, Yuan Liu, Shuaifei Huang et al. · 0 citations