Longitudinal Functional MRI of Motor and Cognitive Recovery Following Stroke: A Review
Bibliographic record
Abstract
Approximately half of all strokes result in moderate-to-severe disability, making stroke the leading cause of long-term disability in North America. Functional magnetic resonance imaging (fMRI) has emerged as a powerful tool to investigate functional reorganization, temporary or permanent, during the recovery of motor and cognitive functions following stroke, as a means to potentially predict patient outcome and guide rehabilitation. Recently, fMRI studies of stroke recovery have been moving towards a clinical focus, with increased emphasis on longitudinal investigations of recovery. In addition, the integration of fMRI with other imaging modalities such as electroencephalography (EEG) and near-infrared (NIR) diffuse optical tomography is becoming increasingly important to further investigate the spatiotemporal evolution of brain function following stroke. This article will review the literature of longitudinal studies of motor and cognitive recovery using fMRI, as well as discuss issues regarding the possible implementation of fMRI for longitudinal studies of stroke recovery in individual patients. Keywords: fMRI, stroke, motor, language, memory, recovery
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".