Supplementary file 1_Electrophysiological signature of stroke recovery: investigating EEG biomarkers for prognostic insights.pdf

An integrated framework capturing spatiotemporal EEG dynamics would help clarify how these networks change during recovery.</p>Methods<p>We analysed resting-state EEG from stroke patients at 1 week (Session 1) and three months (Session 2) post-stroke to investigate electrophysiological biomarkers of motor recovery, indexed by change in the Fugl-Meyer scale (ΔFM).

We quantified relative alpha-band power, microstate metrics (mean duration, complexity, and transition probabilities), and measures of metastability and synchrony derived from the Kuramoto Order Parameter.</p>Results:s<p>Change in relative alpha power emerged as the strongest single correlate of motor improvement, accounting for the largest proportion of variance among the EEG measures examined. Metastability and synchrony did not individually reach statistical significance but showed moderate positive correlations with ΔFM, particularly in the alpha and theta bands, and added 26% explained variance in ΔFM when combined with alpha power.