Long-Lasting, Context-Dependent Modification of Stepping in the Cat After Repeated Stumbling-Corrective Responses
Bibliographic record
Abstract
A consistent feature of animal locomotion is the capacity to maintain stable movements in changing environments. Here we describe long-term modification of the swing movement of the hind leg in cats in response to repeatedly impeding the movement of the leg. While studying phase transitions in the hind legs, we discovered that repetitively evoking the stumbling-corrective reaction led to long-lasting increases in knee flexion and step height during swing to avoid the impediment. These increases were apparent after nearly 20 stimuli and maximal after about 120 stimuli and, in some animals, they persisted for > or =24 h after presentation of the stimuli. Furthermore, these long-lasting changes were context dependent and did not generalize to other environments; when walking was observed in an environment distinct from that used in training, the hind-limb kinematics returned to normal. To gain insight into what regions of the nervous system might be involved in this long-term modification, we examined the changes in stepping in decerebrate cats after multiple perturbed steps. In this situation, there was a short-term increase in step height, although this increase was smaller than that evoked in intact animals and persisted for <1 min after termination of the stimuli. Thus induction of the long-term increase in step height requires the forebrain. We propose that the conditioned change in leg movement is related to a general ability of animals to adapt locomotor movements to new features of the environment.
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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) | 0.001 | 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".