Task-specific compensation and recovery following focal motor cortex lesion in stressed rats
Bibliographic record
Abstract
One reason for the difficulty to develop effective therapies for stroke is that intrinsic factors, such as stress, may critically influence pathological mechanisms and recovery. In cognitive tasks, stress can both exaggerate and alleviate functional loss after focal ischemia in rodents. Using a comprehensive motor assessment in rats, this study examined if chronic stress and corticosterone treatment affect skill recovery and compensation in a task-specific manner. Groups of rats received daily restraint stress or oral corticosterone supplementation for two weeks prior to a focal motor cortex lesion. After lesion, stress and corticosterone treatments continued for three weeks. Motor performance was assessed in two skilled reaching tasks, skilled walking, forelimb inhibition, forelimb asymmetry and open field behavior. The results revealed that persistent stress and elevated corticosterone levels mainly limit motor recovery. Treated animals dropped larger amounts of food in successful reaches and showed exaggerated loss of forelimb inhibition early after lesion. Stress also caused a moderate, but non-significant increase in infarct size. By contrast, stress and corticosterone treatments promoted reaching success and other quantitative measures in the tray reaching task. Comparative analysis revealed that improvements are due to task-specific development of compensatory strategies. These findings suggest that stress and stress hormones may partially facilitate task-specific and adaptive compensatory movement strategies. The observations support the notion that hypothalamic-pituitary-adrenal axis activation may be a key determinant of recovery and motor system plasticity after ischemic stroke.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".