Musicians show greater cross-modal integration, intermodal integration, and specialization in working memory than non-musicians
Bibliographic record
Abstract
Theories of working memory (WM) often distinguish between a central component and peripheral components for verbal and visual information. In the present study, we tested whether musicians differed from non-musicians on WM capacity and structure, with a particular focus on motor memory. We compared individuals with instrumental music training ( n = 91) to those without musical training ( n = 99) on seven WM tasks, measuring visual, verbal, and motor memory. The results showed that the musicians only rarely outperformed non-musicians on WM tasks. As for memory structure, a principal components analysis revealed that the seven tasks loaded onto different components for non-musicians and musicians. In musicians, scores loaded onto three components that represent motor–visual memory, verbal memory, and memory for the movements of others. In contrast, there were only two extracted components for non-musicians. These results suggest that music training leads to greater cross-modal and intermodal integration in WM, as well as specialization within motor 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".