Stroke frequently results in long-term upper limb (UL) motor impairments, limiting independence and quality of life. Accurate prediction of recovery trajectories is essential for personalizing rehabilitation strategies. While structural brain metrics such as corticospinal tract (CST) integrity have been widely studied, they incompletely explain motor outcome variability. Functional brain activity, quantified by sensorimotor activity in the beta (β) frequency range has emerged as a promising biomarker of motor system integrity and plasticity potential. This study assessed in 30 acute stroke survivors and 26 healthy controls how combining functional and structural metrics of brain function relates to initial motor severity and subsequent recovery, using clinical MRI/CT and electroencephalography during passive finger movement and rest. Structurally, grey and white matter damage were associated with initial severity. No associations with recovery were found for structural metrics alone. Functionally, β-activity in response to passive movement, and resting state activity were related to recovery, independent of initial impairment. Multivariate regression revealed that combining initial severity, structural information (CST damage) and brain function (sensorimotor β activity) provided the most accurate prediction of both global and UL-specific recovery (R2 = 80.1% and 74.3%, respectively). These findings underscore the importance of integrating functional and structural neural markers for improved stroke outcome prediction.

The authors have declared no competing interest.

The study and CZ were supported by Brain Research UK (201718-13). L.C.M. was supported by the Medical Research Council (MR/N013867/1). This work was supported by a Senior Research Fellowship to Charlotte J Stagg by the Wellcome Trust (224430/Z/21/Z). This research was supported by the NIHR Oxford Health Biomedical Research Centre (NIHR203316). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The Centre for Integrative Neuroimaging (203139/Z/16/Z and 203139/A/16/Z) and the Centre for Human Neuroimaging (203147/Z/16/Z) were supported by core funding from the Wellcome Trust. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

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The Research Ethics Committee of the University College London and the NHS Research Ethics Committee (London - Surrey Research Ethics Committee) approved the study protocol (20/LO/0520), and all subjects provided written informed consent.

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