Synergistic contributions of periodic and aperiodic cortical activity to motor recovery prediction after stroke
Abstract
Functional motor recovery in chronic stroke can be promoted by intensive exercise aided by neurotechnology, yet reliable physiological markers to predict recovery remain limited. Scalp electroencephalography (EEG) is widely used in clinical routines, but conventional band-power metrics conflate oscillatory (periodic) and broadband (aperiodic) activity, limiting their interpretability. Here, we tested whether EEG spectral profiles predict motor recovery in chronic stroke. Resting-state EEG (1 min) was recorded at admission and discharge using a portable system (N = 41) and parameterized with a spectral decomposition model. Parameters were examined in relation to motor improvement, as indexed by gain in a clinical score, and used to construct a prediction model. Ipsilesional periodic activity at the individual alpha frequency (IAF) significantly increased after rehabilitation (P = 0.024) and correlated with motor improvement (r = 0.39, P = 0.010). A stepwise regression model identified higher IAF peaks, steeper aperiodic slopes, and their interaction as predictors of recovery (Severe group: R2 = 0.53, P = 0.003; balanced accuracy = 88%). The model outperformed a delta–alpha ratio–based approach commonly used in stroke prognosis. These findings indicate that the synergistic interaction between periodic and aperiodic activity provides a mechanistically meaningful and clinically relevant biomarker of residual plasticity, supporting individualized rehabilitation strategies in chronic stroke.
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BibTeX
@article{iwama2026synergistic,
title = {{Synergistic contributions of periodic and aperiodic cortical activity to motor recovery prediction after stroke}},
author = {Seitaro Iwama and Daisuke Ito and Takayuki Kamimoto and Arisa Kawabata and Junsuke Ito and Tetsuya Tsuji and Junichi Ushiba and Michiyuki Kawakami},
journal = {Brain Communications},
year = {2026},
month = oct,
doi = {10.1093/braincomms/fcag400},
url = {https://doi.org/10.1093/braincomms/fcag400},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Synergistic contributions of periodic and aperiodic cortical activity to motor recovery prediction after stroke
AU - Seitaro Iwama
AU - Daisuke Ito
AU - Takayuki Kamimoto
AU - Arisa Kawabata
AU - Junsuke Ito
AU - Tetsuya Tsuji
AU - Junichi Ushiba
AU - Michiyuki Kawakami
PY - 2026
DA - 2026/10/21
JO - Brain Communications
DO - 10.1093/braincomms/fcag400
UR - https://doi.org/10.1093/braincomms/fcag400
AB - Functional motor recovery in chronic stroke can be promoted by intensive exercise aided by neurotechnology, yet reliable physiological markers to predict recovery remain limited. Scalp electroencephalography (EEG) is widely used in clinical routines, but conventional band-power metrics conflate oscillatory (periodic) and broadband (aperiodic) activity, limiting their interpretability. Here, we tested whether EEG spectral profiles predict motor recovery in chronic stroke. Resting-state EEG (1 min) was recorded at admission and discharge using a portable system (N = 41) and parameterized with a spectral decomposition model. Parameters were examined in relation to motor improvement, as indexed by gain in a clinical score, and used to construct a prediction model. Ipsilesional periodic activity at the individual alpha frequency (IAF) significantly increased after rehabilitation (P = 0.024) and correlated with motor improvement (r = 0.39, P = 0.010). A stepwise regression model identified higher IAF peaks, steeper aperiodic slopes, and their interaction as predictors of recovery (Severe group: R2 = 0.53, P = 0.003; balanced accuracy = 88%). The model outperformed a delta–alpha ratio–based approach commonly used in stroke prognosis. These findings indicate that the synergistic interaction between periodic and aperiodic activity provides a mechanistically meaningful and clinically relevant biomarker of residual plasticity, supporting individualized rehabilitation strategies in chronic stroke.
SN - 2632-1297
ER -