Contextual learning and obstacle memory in the walking cat
Bibliographic record
Abstract
Animals in their natural environments display a remarkably diverse variety of walking patterns. Although some of this diversity is generated by alterations in feedback from the moving limbs, animals can modify their walking in many ways that cannot be directly attributed to this sensory feedback. For example, animals and humans can learn to associate a particular environment with disturbances that were experienced there earlier, and alter their stepping accordingly even after the disturbance has ceased. Another relevant example is that walking animals are aware of the locations of obstacles around them, and use this awareness to alter their stepping patterns even when there is no visual information available about the location of the obstacles relative to the body. In this article, we discuss recent work from our laboratory that addresses these two topics. First, we report that perturbing walking cats in a consistent manner evokes long-lasting changes to the walking pattern that are expressed only in the context in which walking was disturbed. Secondly, we show that cats that have stepped over an obstacle remember the location of that obstacle relative to the body during long delays, and can use that memory to guide stepping. The general theme of this research is that sensory inputs that signal context-the visual and auditory environment that surrounds an animal-play an important role in shaping the basic pattern of locomotion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".