Recovery of locomotion after partial spinal cord lesions in cats: assessment using behavioral, electrophysiological and imaging techniques
Bibliographic record
Abstract
This short review summarizes experimental findings made after spinal cord injury, mainly in cats. After a complete spinal injury, cats re-express hindlimb locomotion after 2-3 weeks because of a spinal locomotor circuitry named the central pattern generator or CPG. To investigate whether such circuits are also implicated in the recovery of locomotion after partial spinal lesions, we have used a dual spinal lesion paradigm. Essentially, after an initial unilateral hemisection, cats spontaneously recover quadrupedal locomotion. When a complete section is then performed 3 weeks after this hemisection, cats can walk with the hindlimbs within 24 hours compared to 2-3 weeks in cats with single complete spinal lesions demonstrating the importance of spinal mechanisms after partial lesions. Using kinematic and electromyographic methods to evaluate the changes throughout the dual lesion paradigm, we could show that the spinal cord reorganizes spontaneously without locomotor training or with training provided between the partial and complete spinal lesion. To assess spinal lesions we have used histology and magnetic resonance imaging (MRI). We will describe some advanced MRI techniques such as diffusion and magnetization transfer, which provide higher specificity to axon degeneration and demyelination. Examples of advanced MRI techniques in cats and humans are described, including the current limitations and perspectives.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".