Effects of Leg Pedaling on Early Latency Cutaneous Reflexes in Upper Limb Muscles
Bibliographic record
Abstract
The functional coupling of neural circuits between the upper and lower limbs involving rhythmic movements is of interest to both motor control research and rehabilitation science. This coupling can be detected by examining the effect of remote rhythmic limb movement on the modulation of reflex amplitude in stationary limbs. The present study investigated the extent to which rhythmic leg pedaling modulates the amplitude of an early latency (peak 30-70 ms) cutaneous reflex (ELCR) in the upper limb muscles. Thirteen neurologically intact volunteers performed leg pedaling (60 or 90 rpm) while simultaneously contracting their arm muscles isometrically. Control experiments included isolated isometric contractions and discrete movements of the leg. ELCRs were evoked by stimulation of the superficial radial nerve with a train of rectangular pulses (three pulses at 333 Hz, intensity 2.0- to 2.5-fold perceptual threshold). Reflex amplitudes were significantly increased in the flexor carpi radialis and posterior deltoid and significantly decreased in the biceps brachii muscles during leg pedaling compared with that during stationary isometric contraction of the lower leg muscles. This effect was also sensitive to cadence. No significant modulation was seen during the isometric contractions or discrete movements of the leg. Additionally, there was no phase-dependent modulation of the ELCR. These findings suggest that activation of the rhythm generating system of the legs affects the excitability of the early latency cutaneous reflex pathways in the upper limbs.
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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".