Waiting for a hand: saccadic reaction time increases in proportion to hand reaction time when reaching under a visuomotor reversal
Bibliographic record
Abstract
Although eye movement onset typically precedes hand movement onset when reaching to targets presented in peripheral vision, arm motor commands appear to be issued at around the same time, and possibly in advance, of eye motor commands. A fundamental question, therefore, is whether eye movement initiation is linked or yoked to hand movement. We addressed this issue by having participants reach to targets after adapting to a visuomotor reversal (or 180° rotation) between the position of the unseen hand and the position of a cursor controlled by the hand. We asked whether this reversal, which we expected to increase hand reaction time (HRT), would also increase saccadic reaction time (SRT). As predicted, when moving the cursor to targets under the reversal, HRT increased in all participants. SRT also increased in all but one participant, even though the task for the eyes-shifting gaze to the target-was unaltered by the reversal of hand position feedback. Moreover, the effects of the reversal on SRT and HRT were positively correlated across participants; those who exhibited the greatest increases in HRT also showed the greatest increases in SRT. These results indicate that the mechanisms underlying the initiation of eye and hand movements are linked. In particular, the results suggest that the initiation of an eye movement to a manual target depends, at least in part, on the specification of hand movement.
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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 | 0.005 |
| 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) | 0.006 | 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".