Perceived Motor Synchrony With the Beat is More Strongly Related to Groove Than Measured Synchrony
Bibliographic record
Abstract
The sensation of groove can be defined as the pleasurable urge to move to rhythmic music. When moving to the beat of a rhythm, both how well movements are synchronized to the beat, and the perceived difficulty in doing so, are associated with groove. Interestingly, when tapping to a rhythm, participants tend to overestimate their synchrony, suggesting a potential discrepancy between perceived and measured synchrony, which may impact their relative relation with groove. However, these relations, and the influence of syncopation and musicianship on these relations, have yet to be tested. Therefore, we asked participants to listen to 50 drum patterns with varying rhythmic complexity and rate their sensation of groove. They then tapped to the beat of the same drum patterns and rated how well they thought their taps synchronized with the beat. Perceived synchrony showed a stronger relation with groove ratings than measured synchrony and syncopation, and this effect was strongest for medium complexity rhythms. We interpret these results in the context of meter-based temporal predictions. We propose that the certainty of these predictions determine the weight and number of movements that are perceived as synchronous and thus reflect rewarding prediction confirmations.
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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 | 0.014 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".