New Perspectives on Music in Rehabilitation of Executive and Attention Functions
Bibliographic record
Abstract
Modern music therapy, starting around the middle of the twentieth century was primarily conceived to promote emotional well-being and to facilitate social group association and integration. Therefore, it was rooted mostly in social science concepts. More recently, music as therapy began to move decidedly toward perspectives of neuroscience. This has been facilitated by the advent of neuroimaging techniques that help uncover the therapeutic mechanisms for non-musical goals in the brain processes underlying music perception, cognition, and production. In this paper, we focus on executive function (EF) and attentional processes (AP) that are central for cognitive rehabilitation efforts. To this end, we summarize existing behavioral as well as neuroimaging and neurophysiological studies in musicians, non-musicians, and clinical populations. Musical improvisation and instrumental playing may have some potential for EF/AP stimulation and neurorehabilitation. However, more neuroimaging studies are needed to investigate the neural mechanisms for the active musical performance. Furthermore, more randomized clinical trials combined with neuroimaging techniques are warranted to demonstrate the specific efficacy and neuroplasticity induced by music-based interventions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".