Enriched Rehabilitative Training Promotes Improved Forelimb Motor Function and Enhanced Dendritic Growth after Focal Ischemic Injury
Bibliographic record
Abstract
Chronic impairment of forelimb and digit movement is a common problem after stroke that is resistant to therapy. Previous studies have demonstrated that enrichment improves behavioral outcome after focal ischemia; however, postischemic enrichment alone is not capable of enhancing fine digit and forelimb function. Therefore, we combined environmental enrichment with daily skilled-reach training to assess the effect of intensive task-specific rehabilitation on long-term functional outcome. Rats were subjected to either endothelin-1-induced focal ischemia or sham surgery and subsequently designated to enriched-rehabilitation or standard-housing treatment groups starting 15 d after ischemia. Functional assessment of the affected forelimb at 4 and 9 weeks after treatment revealed that ischemic plus enrichment (IE) animals had improved approximately 30% on the staircase-reaching task and were indistinguishable from sham animals for both latency and foot faults in a beam-traversing task. In contrast, ischemic plus standard (IS) animals remained significantly impaired on both tasks. Interestingly, both ischemic groups (IE and IS) relied on the nonaffected forelimb during upright weight-bearing movements, a pattern that persisted for the duration of the experiment. Dendritic arborization of layer V pyramidal cells within the undamaged motor cortex was examined using a Golgi-Cox procedure. IE animals showed enhanced dendritic complexity and length compared with both IS and sham groups. These results suggest that enrichment combined with task-specific rehabilitative therapy is capable of augmenting intrinsic neuronal plasticity within noninjured, functionally connected brain regions, as well as promoting enhanced functional outcome.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".