Heteronymous reflex connections in human upper limb muscles in response to stretch of forearm muscles
Bibliographic record
Abstract
Torque motor produced stretch of upper limb muscles results in two distinct reflex peaks in the electromyographic activity. Whereas the short-latency reflex (SLR) response is mediated largely by the spinal monosynaptic reflex pathway, the longer-latency reflex (LLR) is suggested to involve a transcortical loop. For the SLRs, patterns of heteronymous monosynaptic Ia connections have been well-studied for a large number of muscles in the cat and in humans. For LLRs, information is available for perturbations to proximal joints, although the protocols for most of these studies did not focus on heteronymous connections. The main objective of the present study was to elicit both SLRs and LLRs in wrist flexors and extensors and to examine heteronymous connections from these muscles to elbow flexors (biceps brachii; BiBr) and extensors (triceps brachii; TriBr) and to selected distal muscles, including abductor pollicis longus (APL), first dorsal interosseous (FDI), abductor digiti minimi (ADM), and Thenars. The stretch of wrist flexors produced SLR and LLR peaks in APL, FDI, ADM, Thenars, and BiBr while simultaneously inducing inhibition of wrist extensors and TriBr. When wrist extensors were stretched, SLR and LLR peaks were observed in TriBr, whereas the primary wrist flexors, APL and BiBr, were inhibited; response patterns of FDI, ADM, and Thenars were less consistent. The main conclusions from the observed data are that: 1) as in the cat, afferents from wrist flexors and extensors make heteronymous connections with proximal and distal upper limb muscles; and 2) the strength of heteronymous connections is greater for LLRs than SLRs in the distal muscles, whereas the opposite is true for the proximal muscles. In the majority of observations, SLR and LLR excitatory peaks were observed together. However, on occasion, LLRs were observed without the SLR response in hand muscles when wrist extensors were stretched.
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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".