Contribution of Cutaneous Inputs From the Hindpaw to the Control of Locomotion. II. Spinal Cats
Bibliographic record
Abstract
The goal of these experiments was to define the contribution of hindpaw cutaneous inputs in the expression of spinal locomotion in cats. In 3 cats, some (n = 1) or all (n = 2) cutaneous nerves were cut bilaterally at ankle level before spinalization. This denervation caused small deficits that were gradually compensated as reported in the companion study. After spinalization, the completely denervated cats never recovered plantar foot placement or weight bearing of the hindquarters despite more than 35 days of treadmill training. Although normal electromyographic rhythmic activity developed at the hip and knee, ankle flexors and extensors were abnormally coactivated during stance. In contrast, the partially denervated cat regained foot placement and weight support 15 days after spinalization. However, after completing the denervation, foot placement and weight bearing were lost as in previous cats. In a 4th cat, spinalization was performed before denervation and the cutaneous nerves were cut sequentially in the right hindlimb only. Rapid locomotor adaptation occurred after cutting the deep peroneal, saphenous, and sural nerves. Later, cutting the superficial peroneal nerve produced paw drag, which was compensated within 8 days. On cutting the last cutaneous nerve (tibial), plantar foot placement was lost despite another 71 days of training. On the one hand, these experiments show that some cutaneous inputs are necessary for appropriate plantar foot placement and weight bearing of the hindquarters during spinal locomotion and, on the other hand, that locomotor compensation to partial cutaneous denervation after spinalization reveals important adaptive capacities of the spinal cord.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".