Central Resetting of Neuromuscular Steady States May Underlie Rhythmical Arm Movements
Bibliographic record
Abstract
Changing the steady-state configuration of the body or its segments may be an important function of central pattern generators for locomotion and other rhythmical movements. Thereby, muscle activation, forces, and movement may emerge following a natural tendency of the neuromuscular system to achieve the current steady-state configuration. To verify that transitions between different steady states occur during rhythmical movements, we asked standing subjects to swing one or both arms synchronously or reciprocally at approximately 0.8 Hz from the shoulder joints. In randomly selected cycles, one arm was transiently arrested by an electromagnetic device. Swinging resumed after some delay and phase resetting. During bilateral swinging, the nonperturbed arm often stopped before resuming swinging at a position that was close to either the extreme forward or the extreme backward arm position observed before the perturbation. Oscillations usually resumed when both arms arrived at similar extreme positions when a synchronous bilateral pattern was initially produced or at the opposite positions if the initial pattern was reciprocal. Results suggest that a central generator controls both arms as a coherent unit by producing transitions between its steady state (equilibrium) positions. By controlling these positions, the system may define the spatial boundaries of movement. At these positions, the system may halt the oscillations, resume them at a new phase (as observed in the present study), or initiate a new motor action. Our findings are relevant to locomotion and suggest that walking may also be generated by transitions between several equilibrium configurations of the body, possibly accomplished by modulation and gating of proprioceptive reflexes.
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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".