Identifying Personalized Brain States Predicting Residual Corticospinal Tract Output After Stroke

Transcranial magnetic stimulation (TMS) interventions could feasibly strengthen residual corticospinal tract (CST) connections and promote poststroke hand motor recovery. To maximize the effects of such interventions, they must be delivered during brain activity patterns during which TMS best activates the residual CST and enhances its neural transmission. This approach is termed brain state-dependent TMS. The investigators have recently developed a machine learning framework that identifies personalized brain activity patterns reflecting strong CST activation in neurotypical adults. In this study, the investigators will apply this framework to the poststroke brain for the first time. They will also evaluate relationships between this framework's ability to detect strong and weak CST activation states and measures of CST pathway integrity. Participants will visit the laboratory for two days of testing that are separated by at least one night of sleep. On Day 1, participants will provide their informed consent. The MacArthur Competence Assessment Tool and the Frenchay Aphasia Screening Test will be used to evaluate consent capacity and confirm the presence of expressive aphasia as needed. Afterwards, participants will complete eligibility screening and clinical assessment of upper extremity motor impairment, motor function, and disability using the Upper Extremity Fugl-Meyer Assessment, the Wolf Motor Function Test, and the Modified Rankin Scale. Participants will then be scr…

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