Voluntary and Involuntary Movements Widen the Window of Subjective Simultaneity
Bibliographic record
Abstract
Forming a coherent percept of an event requires different sensory inputs originating from the event to be bound. Perceiving synchrony aids in binding of these inputs. In two experiments, we investigated how voluntary movements influence the perception of simultaneity, by measuring simultaneity judgments (SJs) for an audiovisual (AV) stimulus pair triggered by a voluntary button press. In Experiment 1, we manipulated contiguity between the action and its consequences by introducing delays between the button press and the AV stimulus pair. We found a widened window of subjective simultaneity (WSS) when the action-feedback relationship was time contiguous. Introducing a delay narrowed the WSS, suggesting that the wider WSS around the time of an action might facilitate perception of simultaneity. In Experiment 2, we introduced an involuntary condition using an externally controlled button to assess the influence of action-related predictive processes on SJs. We found a widened WSS around the action time, regardless of movement type, supporting the influence of causal relations in the perception of synchrony. Interestingly, the slopes of the psychometric functions in the voluntary condition were significantly steeper than the slopes in the involuntary condition, suggesting a role of action-related predictive mechanisms in making SJs more precise.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".