Music and Dance Training are not Uniquely Associated with Memory Skills
Bibliographic record
Abstract
Music training is robustly associated with cognitive skills, and with tonal and verbal memory more specifically. However, it is unclear whether these associations reflect near or far transfer and/or whether they indicate pre-existing differences between those who do or do not take music lessons for long durations. Dance training may similarly rely on or train visuospatial memory abilities and produce exercise-induced benefits for working memory, but there is far less research on its associations with cognition. In Study 1, women with varying durations of formal music and dance experience completed measures of visual and auditory memory, general intelligence, demographics, and personality. Music training was associated with auditory immediate and delayed memory, as well as visual working memory, but all associations disappeared when other variables were held constant. Furthermore, dance training was not associated with any memory measure. Study 2 was similar but focused on visual memory and included both men and women. We replicated the simple association between duration of music training and visual working memory, which once again ceased to remain significant when controlling for other variables. Similarly, dance training failed to correlate with any visual memory measure despite the use of more valid visual memory tasks. Our findings suggest that memory advantages among musicians most likely result from pre-existing differences rather than near transfer and provide no evidence of transfer from dance training to visual memory.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".