Amateur Singing Benefits Speech Perception in Aging Under Certain Conditions of Practice: Behavioural and Neurobiological Mechanisms.
Bibliographic record
Abstract
Abstract Limited evidence has shown that practising musical activities in aging, such as choral singing, could lessen age-related speech perception in noise (SPiN) difficulties. However, the robustness and underlying mechanism of action of this phenomenon remain unclear. In this study, we used surface-based morphometry combined with a moderated mediation analytic approach to examine whether singing-related plasticity in auditory and dorsal speech stream regions can mitigate age-related SPiN difficulties. 36 choral singers and 36 non-singers aged 20–87 years underwent cognitive, auditory, and SPiN assessments. Our results provide important new insights into experience-dependent plasticity by revealing that, under certain conditions of practice, amateur choral singing is associated with age-dependent structural plasticity within auditory and dorsal speech regions, which is associated with better SPiN performance in aging. Specifically, the conditions of practice that were beneficial for SPiN included frequent weekly practice at home, several hours of weekly group singing practice, singing in multiple languages, and having received formal singing training. These results suggest that the effect of amateur choral singing on SPiN is related to a dual mechanism involving auditory processing and auditory-motor integration and may be dose dependent, with more intense singing associated with greater benefit. Our results thus reveal that the relationship between musical practice and SPiN is complex, and underscore the importance of considering musical practice behaviours in understanding the effects of musical activities on the brain-behaviour relationship.
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 | 0.001 |
| 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 | 0.001 |
| 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".