Neural Adaptation in the Generation of Rhythmic Behavior
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Motor systems can adapt rapidly to changes in external conditions and to switching of internal goals. They can also adapt slowly in response to training, alterations in the mechanics of the system, and any changes in the system resulting from injury. This article reviews the mechanisms underlying short- and long-term adaptation in rhythmic motor systems. The neuronal networks underlying the generation of rhythmic motor patterns (central pattern generators; CPGs) are extremely flexible. Neuromodulators, central commands, and afferent signals all influence the pattern produced by a CPG by altering the cellular and synaptic properties of individual neurons and the coupling between different populations of neurons. This flexibility allows the generation of a variety of motor patterns appropriate for the mechanical requirements of different forms of a behavior. The matching of motor output to mechanical requirements depends on the capacity of pattern-generating networks to adapt to slow changes in body mechanics and persistent errors in performance. Afferent feedback from body and limb proprioceptors likely plays an important role in driving these long-term adaptive processes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it