Subcortical gray matter aging and attentional control in amateur musicians and nonmusicians
Bibliographic record
Abstract
Aging is associated with declines in attentional control. While most studies have explored the relationship between brain structure and attention at the cortical level, subcortical structures remain largely overlooked. Leisure activities, such as musical practice, are thought to promote brain reorganization and help preserve cognitive function in aging. However, evidence for such effects at the subcortical level remains limited. In this cross-sectional study, we examined the relationship between age, subcortical gray matter, and attentional control in amateur musicians and nonmusicians. A total of 108 adults (20-88 years) were recruited, including 34 singers, 37 instrumentalists, and 37 active nonmusicians. Participants completed an auditory selective attention task and a visual inhibition task. Anatomical magnetic resonance imaging (MRI) images were acquired to examine the relationship between subcortical volumes and attentional measures. Our results indicate that aging is associated with worse attentional control and smaller subcortical volumes. While no group differences in subcortical volume were observed, significant interactions emerged between musical activity and subcortical volume in relation to attentional control, particularly in inhibition. Notably, in singers, greater musical experience and smaller subcortical volumes were linked to better inhibition. These results refine our understanding of subcortical contributions to attentional control in aging musicians and nonmusicians.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".