Recovery of skilled reaching following motor cortex stroke: do residual corticofugal fibers mediate compensatory recovery?
Bibliographic record
Abstract
Motor cortex (MC) injury impairs skilled reaching in rats, but success scores are eventually restored to approximate preoperative levels. The improvement is attributed to compensatory strategies, such as substituting trunk rotations for the chronically lost rotatory movement of the forelimb, that occur during transport and withdrawal. The present study examined the contributions of the rostral motor cortex (RMC) and the caudal motor cortex (CMC) to skilled reaching performance. The study also examined the role of the ipsilateral and the contralateral hemispheres in supporting the spontaneous recovery. Rats were trained to reach for single food pellets, and their recovery from partial or complete MC injury was documented with quantitative scores and movement element measures in three experiments: (1) devascularization of the CMC, or the RMC, or both, in the hemisphere contralateral to the reaching paw; (2) additional lesions to the CMC and RMC injuries such that the conjoint damage amounted to an MC lesion; and (3) MC lesion followed by damage in the neocortex lateral to the injury or in the opposite MC. The results showed that the CMC made the main contribution to skilled reaching performance, and that there was a lesser contribution by the RMC. MC damage was exacerbated by additional damage to the ipsilateral neocortex as compared to the contralateral neocortex. The results are discussed in relation to the idea that the involvement of the neocortical areas in skilled reaching performance and its recovery is proportional to the region from which corticospinal projections originate.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| 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".