Rapid Motor Responses Are Appropriately Tuned to the Metrics of a Visuospatial Task
Bibliographic record
Abstract
Considerable research has established that rapid motor responses (traditionally called reflexes), can be modified by a subject's voluntary goals. Here, we expand on past observations using verbal instructions by defining the voluntary goal via visual target position. This approach allowed us to objectively enforce task adherence and explore a richer set of variables, such as target direction and distance, metrics that modify voluntary control and that--according to our hypothesis--will influence rapid motor responses. Our first experiment tested whether upper-limb responses are categorically modulated by target direction by placing targets such that the same perturbation could push the hand into one target and out of the other, a spatial analogue to "resist/yield" verbal instructions. Consistent with these classical results, we found that the short-latency rapid response (R1, 20-45 ms) was not modulated by target direction, whereas long-latency rapid responses (R2/R3, 45-105 ms) were modified in a manner approaching the voluntary response (VOL, 120-180 ms). Our second experiment tested whether upper-limb responses are continuously modulated by target distance by distributing five targets along one axis centered on the hand. Here, the long-latency and voluntary response mirrored the task demands by increasing activity in a graded fashion with increasing target distance. Our final experiment explored how upper-limb responses incorporate two-dimensional spatial information by placing targets radially around the hand. Notably, long-latency responses exhibited smooth tuning functions to target direction that were similar to those observed for the voluntary response. Taken together, these results illustrate the flexibility of long-latency rapid responses and emphasize their similarity to later voluntary responses.
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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 | 0.001 | 0.004 |
| 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) | 0.002 | 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".