Feedback responses rapidly scale with the urgency to correct for external perturbations
Bibliographic record
Abstract
Healthy subjects can easily produce voluntary actions at different speeds and with varying accuracy requirements. It remains unknown whether rapid corrective responses to mechanical perturbations also possess this flexibility and, thereby, contribute to the capability expressed in voluntary control. Paralleling previous studies on self-initiated movements, we examined how muscle activity was impacted by either implicit or explicit criteria affecting the urgency to respond to the perturbation. Participants maintained their arm position against torque perturbations with unpredictable timing and direction. In the first experiment, the urgency to respond was explicitly altered by varying the time limit (300 ms vs. 700 ms) to return to a small target. A second experiment addresses implicit urgency criteria by varying the radius of the goal target, such that task accuracy could be achieved with less vigorous corrections for large targets than small target. We show that muscle responses at ∼60 ms scaled with the task demand. Moreover, in both experiments, we found a strong intertrial correlation between long-latency responses (∼50-100 ms) and the movement reversal times, which emphasizes that these rapid motor responses are directly linked to behavioral performance. The slopes of these linear regressions were sensitive to the experimental condition during the long-latency and early voluntary epochs. These findings suggest that feedback gains for very rapid responses are flexibly scaled according to task-related urgency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".