A Trial-by-Trial Window into Sensorimotor Transformations in the Human Motor Periphery
Bibliographic record
Abstract
UNLABELLED: The appearance of a novel visual stimulus generates a rapid stimulus-locked response (SLR) in the motor periphery within 100 ms of stimulus onset. Here, we recorded SLRs from an upper limb muscle while humans reached toward (pro-reach) or away (anti-reach) from a visual stimulus. The SLR on anti-reaches encoded the location of the visual stimulus rather than the movement goal. Further, SLR magnitude was attenuated when subjects reached away from rather than toward the visual stimulus. Remarkably, SLR magnitudes also correlated with reaction times on both pro-reaches and anti-reaches, but did so in opposite ways: larger SLRs preceded shorter latency pro-reaches but longer latency anti-reaches. Although converging evidence suggests that the SLR is relayed via a tectoreticulospinal pathway, our results show that task-related signals modulate visual signals feeding into this pathway. The SLR therefore provides a trial-by-trial window into how visual information is integrated with cognitive control in humans. SIGNIFICANCE STATEMENT: The presentation of a visual stimulus elicits a trial-by-trial stimulus-locked response (SLR) on the human limb within 100 ms. Here, we show that the SLR continues to reflect stimulus location even when subjects move in the opposite direction (an anti-reach). Remarkably, the attenuation of SLR magnitude reflected the cognitive control required to generate a correct anti-reach, with greater degrees of attenuation preceding shorter-latency anti-reaches and no attenuation preceding error trials. Our results are strikingly similar to neurophysiological recordings in the superior colliculus of nonhuman primates generating anti-saccades, implicating the tectoreticulospinal pathway. Measuring SLR magnitude therefore provides an unprecedented trial-by-trial opportunity to assess the influence of cognitive control on the initial processing of a visual stimulus in humans.
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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 | 0.002 |
| 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) | 0.004 | 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".