Animal Models for Studying Potential Training Strategies in Persons with Spinal Cord Injury
Bibliographic record
Abstract
In the late 1980s, it was clearly demonstrated that adult spinal cats can be re-trained to walk after a complete spinal cord transection, using treadmill training. This has led to profound changes in the rehabilitation of persons with spinal cord injury. The use of animal models to study training-induced locomotor plasticity after spinal cord injury has expanded since this original demonstration. The goal of the present review is to summarize findings obtained with these animal models that may be of relevance to the re-training of humans with spinal cord injury. From the complete spinal cord transection models, adaptive capacity, retention of training, task-specificity, role of cutaneous inputs, effect of training with robotic devices, and spinal cord stimulation will be discussed. From the partial spinal lesion models, the effect of ventral or dorsal lesions of the cord will be presented. Finally, the effects of drugs on training will be compared between the complete and partial spinal lesions models.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".