A common neural element receiving rhythmic arm and leg activity as assessed by reflex modulation in arm muscles
Bibliographic record
Abstract
Neural interactions between regulatory systems for rhythmic arm and leg movements are an intriguing issue in locomotor neuroscience. Amplitudes of early latency cutaneous reflexes (ELCRs) in stationary arm muscles are modulated during rhythmic leg or arm cycling but not during limb positioning or voluntary contraction. This suggests that interneurons mediating ELCRs to arm muscles integrate outputs from neural systems controlling rhythmic limb movements. Alternatively, outputs could be integrated at the motoneuron and/or supraspinal levels. We examined whether a separate effect on the ELCR pathways and cortico-motoneuronal excitability during arm and leg cycling is integrated by neural elements common to the lumbo-sacral and cervical spinal cord. The subjects performed bilateral leg cycling (LEG), contralateral arm cycling (ARM), and simultaneous contralateral arm and bilateral leg cycling (A&L), while ELCRs in the wrist flexor and shoulder flexor muscles were evoked by superficial radial (SR) nerve stimulation. ELCR amplitudes were facilitated by cycling tasks and were larger during A&L than during ARM and LEG. A low stimulus intensity during ARM or LEG generated a larger ELCR during A&L than the sum of ELCRs during ARM and LEG. We confirmed this nonlinear increase in single motor unit firing probability following SR nerve stimulation during A&L. Furthermore, motor-evoked potentials following transcranial magnetic and electrical stimulation did not show nonlinear potentiation during A&L. These findings suggest the existence of a common neural element of the ELCR reflex pathway that is active only during rhythmic arm and leg movement and receives convergent input from contralateral arms and legs.
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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 | 0.000 |
| 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 | 0.000 |
| 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".