Music and metronomes: Source and subjective enjoyability of rhythmic auditory stimuli impact movement performance
Bibliographic record
Abstract
When heard before movement initiation, rhythmic auditory stimuli (RAS) can improve temporal and spatial movement features. RAS, including music, can elicit emotional responses that may alter motor performance. The current experiment used two RAS (metronome and drum beats) that were heard before a goal-directed reaching movement to one of two targets in left and right hemispace. Participants rated subjective enjoyability of each condition on a 5-point Likert scale. We hypothesized participants would enjoy the drum more than the metronome, leading to improved performance with the drum. Twenty-one young adults performed 24 trials in each condition: simple metronome, complex metronome, simple drum, complex drum and no sound, all with and without vision. Conditions were blocked and counterbalanced and target location was randomized. Movements were captured with an Optotrak 3D Investigator (NDI) and vision was occluded upon movement initiation with Visual Occlusion Spectacles (Translucent Technologies Inc.). Dependent variables were analysed using a 3 sound (no sound, metronome, drum) by 2 vision repeated measures ANOVA. Spearman's correlation coefficient was used to compare Likert ratings and performance between drum and metronome conditions. Metronome and drum conditions elicited shorter reaction times (RT) compared to no sound, however, the metronome elicited more consistent RTs. The drum led to higher peak velocities compared to the metronome but no differences in endpoint accuracy. Participants rated the drum more enjoyable compared to the metronome, which was moderately correlated to improved performance in RT. Therefore, the source and subjective enjoyability of RAS can impact performance in a goal-directed reaching task.Acknowledgments: Funding for this project was provided by the Natural Sciences and Engineering Research Council of Canada.
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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 | 0.003 |
| 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) | 0.004 | 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".