Effects of Ankle and Hip Muscle Afferent Inputs on Rhythm Generation During Fictive Locomotion
Bibliographic record
Abstract
Hip position and loading of limb extensors are major sensory cues for the initiation and duration of different phases during walking. Although these inputs have pathways projecting to the locomotor rhythm generator, their effects may vary in different parts of the locomotor cycle. In the present study, the plantaris (Pl), sartorius (Sart), rectus femoris (RF), and caudal gluteal (cGlu) nerves were stimulated at group I and/or group II strength during spontaneous fictive locomotion in 16 adult decerebrate cats. These nerves supply muscles that extend the ankle (Pl), flex the hip (Sart, RF), or extend the hip (cGlu). Stimuli were given at six epochs of the locomotor cycle to evaluate when they access the rhythm generator. Group I afferents from Pl nerve always reset the locomotor rhythm; stimulation during extension prolonged cycle period and extension phase duration, while stimulation during flexion terminated flexion and initiated extension. On the other hand, stimulating RF and cGlu nerves only produced significant effects on the rhythm in precise epochs, particularly during mid-flexion and/or mid- to late extension. Stimulating the Sart nerve produced complex effects on the rhythm that were not distributed evenly to all extensor motor pools. The most consistent effect was reduced flexion phase duration with stimulation during flexion, particularly at group II strength, and prolongation of the extension phase but only in late extension. That hip muscle afferents reset the rhythm in only specific epochs of the locomotor cycle suggests that the rhythm generator operates with several subdivisions to determine phase and cycle durations.
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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 | 0.001 |
| 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".