A Model of Persistent Learned Nonuse Following Focal Ischemia in Rats
Bibliographic record
Abstract
BACKGROUND: After hemiplegic stroke, people often rely on their unaffected limb to complete activities of daily living. A component of residual motor dysfunction involves learned suppression of movement, termed learned nonuse. OBJECTIVE: To date, no rodent stroke model of persistent learned nonuse has been described that can facilitate understanding of this phenomenon and test interventions to overcome it. METHODS: Rats were trained in the staircase skilled-reaching and limb use asymmetry (cylinder) tasks. Endothelin-1 was injected into the cortex and striatum to create focal ischemia. Starting 7 days poststroke, half of the rats (ipsilateral training; n = 15) were trained to reach for food reward pellets in the tray-reaching task with the ipsilateral forelimb. Training lasted 20 days. Rats in the control group (control; n = 15) did not receive training. All rats then remained in their home cages for an additional 30 days. Performance on the cylinder and staircase tasks was assessed ~2 months poststroke. RESULTS: Ischemia caused significant functional impairments in all rats. Significant contralateral forelimb skilled-reaching recovery was evident in the control group at 2 months but not the ipsilateral training group. There was no difference in performance in the cylinder task. Similarly, the volume of brain injury (~66 mm(3)) was similar between groups. Ipsilateral forelimb training reduced poststroke motor recovery. CONCLUSION: This rodent model of persistent nonuse after stroke may be used to further understand mechanisms of learned nonuse as well as to evaluate pharmacological and rehabilitation treatments to overcome it.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".