| Sumario: | Purpose: To systematically characterize the cortical dynamics underlying fine hand motor impairment in patients with acute ischemic stroke (AIS) using a multidimensional task-state electroencephalography (EEG) analysis framework. Materials and Methods: Fifteen patients with AIS and sixteen age- and sex-matched healthy controls were enrolled. EEG signals were recorded while participants performed three standardized fine motor tasks, including fist clenching, index finger pointing, and thumb-finger opposition. Source localization, time-frequency analysis, and brain network topology analysis were jointly applied to extract multidimensional electrophysiological features. Correlation analyses were further conducted to examine the relationships between EEG-derived metrics and clinical measures, including muscle strength grading, National Institutes of Health Stroke Scale (NIHSS) scores, and Activities of Daily Living (ADL) scores. Results: Compared with healthy controls, patients with AIS showed abnormal spatiotemporal cortical dynamics during fine hand movements. These abnormalities included delayed movement-related potentials, a shift of alpha- and beta-band event-related desynchronization from contralateral dominance toward more bilateral and diffuse activation, and altered brain network organization characterized by reduced network efficiency and changes in nodal centrality. In addition, EEG-derived features were significantly associated with clinical measures. Specifically, several event-related desynchronization/event-related synchronization (ERD/ERS)-related amplitudes and small-world properties were significantly correlated with muscle strength grading, NIHSS scores, and ADL scores after false discovery rate correction. Conclusion: Multidimensional task-state EEG analysis can characterize cortical activation abnormalities and network reorganization associated with fine hand motor impairment in patients with AIS. The identified EEG-derived metrics may serve as objective markers for post-stroke motor function assessment and recovery monitoring, and may help support individualized rehabilitation evaluation and planning.
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