Reorganization of Brain Function During Force Production After Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Damage to motor areas of the brain caused by stroke can produce devastating motor deficits, including aberrant control of force. Reorganization of brain function is a fundamental mechanism involved in recovery of motor control after stroke, and recent advances in neuroimaging have enabled study of this reorganization. This review focuses on neuroimaging studies that have examined reorganization of brain function during force production and force modulation after stroke. METHODS: The type and extent of reorganization after stroke were characterized by three factors: severity of injury, time after stroke, and impact of therapeutic interventions on brain activation during force production. Twenty-six studies meeting the inclusion criteria could be identified in MEDLINE (1980-2007). RESULTS: Relevant characteristics of studies (lesion location, chronicity of stroke, and motor task) and mapping techniques varied. During force production, increased activation in secondary motor areas occurred in persons with more severe strokes. Reduced recruitment of secondary motor areas during force production was found as a function of increased time since stroke. During force modulation, increased activation in motor areas occurred with greater force generation. Persons with more severe stroke showed greater activation with increasing force compared with persons with less severe stroke. Alteration of brain activation during and after rehabilitative interventions was identified in some studies. DISCUSSION AND CONCLUSION: This systematic review establishes that reorganization of brain function during force production and force modulation can occur after stroke. These findings imply that therapeutic strategies may target brain reorganization to improve force control and functional recovery after stroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".