Locomotor and Reflex Adaptation After Partial Denervation of Ankle Extensors in Chronic Spinal Cats
Bibliographic record
Abstract
This work investigates the capacity of the spinal cord to generate locomotion after a complete spinal section and its ability to adapt its locomotor pattern after a peripheral nerve lesion. To study this intrinsic adaptive capacity, the left lateral gastrocnemius-soleus (LGS) nerve was sectioned in three cats that expressed a stable locomotion following a complete spinal transection. The electromyograph (EMG) of multiple hindlimb muscles and reflexes, evoked by stimulating the left tibial (Tib) nerve at the ankle, were recorded before and after denervation during treadmill locomotion. Following denervation, the mean amplitude of EMG bursts of multiple hindlimb muscles increased during locomotion, similar to what is found after an identical denervation in otherwise intact cats. Reflex changes were noted in ipsilateral flexors, such as semitendinosus and tibialis anterior, but not in the ipsilateral knee extensor vastus lateralis following denervation. The present results demonstrate that the spinal cord possesses the circuitry necessary to mediate increased EMG activity in multiple hindlimb muscles and also to produce changes in reflex pathways after a muscle denervation. The similarity of changes following LGS denervation in cats with an intact and transected spinal cord suggests that spinal mechanisms play a major role in the locomotor adaptation.
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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".