Sensorimotor coupling modulates perceived time and agency across visual perspectives
Bibliographic record
Abstract
Voluntary actions are associated with sense of agency and distortions of perceived duration. This study examined how sensorimotor coupling and visual perspective modulate perceived duration and sense of agency during manual actions in four pre-registered experiments using virtual reality. Participants moved their hands while observing a virtual hand moving (a)synchronously, and evaluated movement duration and their sense of agency. We found that sensorimotor coupling provided by synchronous visual feedback is associated with longer perceived duration relative to action-related time compression, compared with delayed feedback or pre-recorded movements of another person (Experiments 1 and 2). Sensorimotor coupling also modulated sense of agency and may serve as a shared basis for perceived time and agency. Comparable modulations across first- and third-person perspectives (Experiments 1 and 2), anatomical configurations (Experiment 3), and attention on external entities (Experiment 4) suggest a shared predictive system for sensory consequences of self-generated actions and others’ reactions. This modulation was observed irrespective of anatomical configuration and when attention was directed toward objects unrelated to one’s own body, suggesting that the underlying mechanism is not confined to representations specific to the self, but may instead reflect domain-general predictive computations. These findings, together with the virtual reality technique developed, offer new insights into how humans experience passage of time and agency during voluntary action.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".