The Effects of Cardiovascular Exercise on Corticospinal Excitability in People with Subacute Stroke
Bibliographic record
Abstract
ABSTRACT Cardiovascular exercise (CE) shows promise for stroke recovery, partly by inducing neuroplasticity through excitatory neural signaling. While mechanisms are well-documented in animal models, the neurophysiological effects of CE in humans post-stroke—especially in the early subacute phase when the brain may be more responsive—remain unclear. In this study, 76 individuals within 3 months of their first-ever ischemic stroke were randomized to eight weeks of progressive CE using recumbent steppers plus standard care, or standard care alone. Corticospinal excitability (CSE) was assessed bilaterally using single and paired-pulse transcranial magnetic stimulation (TMS) at baseline, four weeks, and eight weeks. TMS was delivered at rest (chronic effect) and following a single high-intensity interval training (HIIT) session (acute effect). A single HIIT session at baseline significantly increased acute CSE in the contralesional hemisphere. However, despite significant improvements in cardiorespiratory fitness—indicating the effectiveness of the CE intervention—CE training did not lead to significant chronic or acute changes in CSE compared to standard care. This is the first study to investigate the effects of CE on CSE in early subacute stroke. Our findings indicate that while CE improves fitness levels during this critical period of recovery, it may have limited effects on CSE. Trial Registration: https://clinicaltrials.gov/study/NCT05076747 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".