Stimulus‐locked responses on human arm muscles reveal a rapid neural pathway linking visual input to arm motor output
Bibliographic record
Abstract
Previous studies have demonstrated that humans are sometimes capable of initiating arm movements towards visual stimuli at extremely short latencies, implying the presence of a short-latency neural pathway linking visual input to limb motor output. However, little is known about the neural mechanisms that underlie such hastened arm responses. One clue may come from recent demonstrations that the appearance of a visual target can elicit a rapid response in neck muscles that is time-locked to target appearance and functionally relevant for orienting gaze (head and eye) towards the target. Because oculomotor structures thought to contribute to 'visual responses' on neck muscles also target some arm muscles via a tecto-reticulo-spinal pathway, we hypothesized that a similar visual response would be present in arm muscles. Our results were consistent with this hypothesis as we observed the presence of rapid arm muscle activity (<100 ms latency) that was time-locked to target appearance and not movement onset. We further found that the visual response in arm muscles: (i) was present only when an immediate reach towards the target was required; (ii) had a magnitude that was predictive of reaction time; (iii) was tuned to target location in a manner appropriate for moving the arm towards the target; and (iv) was more prevalent in shoulder muscles than elbow muscles. These results provide evidence for a rapid neural pathway linking visual input to arm motor output and suggest the presence of a common neural mechanism for hastening eye, head and arm movements.
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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) | 0.005 | 0.001 |
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".