Cardiac Dynamics in Auditory-Motor Synchronization: Roles of Short-Term Training and Rhythm Complexity
Bibliographic record
Abstract
Previous findings suggest that long-term musical training and rhythm complexity may affect performers’ auditory-motor synchrony and their cardiac rhythms. We investigated the effects of short-term training and rhythm complexity on auditory-motor synchronization and cardiac activity as individuals synchronized with auditory rhythms. Forty-two adult participants synchronized their taps with sounded rhythms to form a 2:3 duration ratio (stimulus duration:tap duration) or a 3:2 duration ratio (tap rate held constant across rhythms). Participants received short training with one rhythm and received longer training with the other rhythm. Then, participants completed five experimental trials in which they synchronized their sounded taps with the stimulus rhythm. Cardiac activity was recorded during synchronization. Tapping synchronization was less accurate and more variable for the 3:2 rhythm than the 2:3 rhythm. Linear measures of cardiac activity showed less high-frequency variability during the 3:2 rhythm than the 2:3 rhythm. Behavioral-cardiac correspondences emerged with training: Poorer synchronization was associated with more variable cardiac activity after long training, but not after short training. Finally, there were consistent individual differences in cardiac recurrence and predictability across training conditions. These findings demonstrate both short-term learning effects and rhythm complexity effects on cardiac dynamics during auditory-motor synchronization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".