Endogenous rhythms influence musicians’ and non-musicians’ interpersonal synchrony
Bibliographic record
Abstract
Individuals display considerable rate differences in the spontaneous production of rhythmic behaviors (such as speech, gait, dance). Temporal precision in rhythmic behavior tends to be highest at individuals' spontaneous production rates; musically trained partners with similar spontaneous rates show increased synchrony in joint tasks, consistent with predictions based on intrinsic frequencies of coupled oscillators. We address whether partner-specific influences of intrinsic frequencies are evidenced in musically trained and untrained individuals who tapped a familiar melody at a spontaneous (uncued) rate individually. Each individual then synchronized with a partner from the same musicianship group at an initially cued rate that matched the partners' spontaneous rates. Musically trained partners showed greater synchrony in joint tapping than musically untrained partners. Asynchrony increased in both groups as the partners' difference in individual spontaneous rates increased, with greater impact for musically untrained pairs. Recurrence quantification analysis confirmed that musically untrained individuals demonstrated greater determinism (less flexibility) in their tapping than musically trained individuals. Furthermore, individuals with greater determinism in solo performances demonstrated reduced synchrony in joint performances. These findings suggest that musicians' increased temporal flexibility is associated with decreased endogenous constraints on production rate and greater interpersonal synchrony in musical tasks.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".