Contribution of Hindpaw Cutaneous Inputs to the Control of Lateral Stability During Walking in the Cat
Bibliographic record
Abstract
To delineate the role of cutaneous feedback from the paws in the regulation of balance during walking, we compared the corrective responses of cats to lateral support surface translation before and after cutaneous denervation of the hindpaws. In addition, we compared characteristics of undisturbed walking before and after denervation. Electromyographic and kinematic data were collected from three cats trained to walk across a walkway, the central portion of which could be unexpectedly translated laterally in either direction. Following denervation, all of the cats changed their step width, lowered their pelvis, and spent more time with the hindlegs in double-support when walking across the walkway. When displaced by lateral support surface translations, the denervated cats made larger lateral steps and required more than a single step to regain balance. However, none of the cats fell following the denervation. The appearance and latency of the responses evoked in the hindleg muscles by the perturbations were unaffected by the denervation. However, the amplitude of these responses was affected by the loss of cutaneous inputs. Responses evoked at paw contact were significantly reduced in most muscles in the absence of cutaneous input, whereas responses evoked at end of stance revealed significant increases in gluteus medius activity with little influence on the activity of other muscles. Therefore the loss of cutaneous inputs leads to instability during gait. Although cutaneous feedback from the hindpaws is not essential for triggering corrective responses to support surface disturbances, it appears that cutaneous inputs are important for scaling the responses initiated by other cues.
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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".