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Record W4412449635 · doi:10.1371/journal.pbio.3003247

Long-term musical training can protect against age-related upregulation of neural activity in speech-in-noise perception

2025· article· en· W4412449635 on OpenAlexafffund
Lei Zhang, Bernhard Roß, Yi Du, Claude Alain

Bibliographic record

VenuePLoS Biology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of TorontoBaycrest Hospital
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsFunctional magnetic resonance imagingCognitionCognitive reservePerceptionPsychologyNoise (video)AudiologyTask (project management)Cognitive psychologyAuditory perceptionSpeech perceptionNeuroscienceComputer scienceMedicineArtificial intelligenceCognitive impairment

Abstract

fetched live from OpenAlex

During cognitive tasks, older adults often show increased frontoparietal neural activity and functional connectivity. Cognitive reserve accrued from positive life choices like long-term musical training can provide additional neural resources to help cope with the effect of aging. However, the relationship between cognitive reserve and upregulated neural activity in older adults remains poorly understood. In this study, we measured brain activity using functional magnetic resonance imaging during a speech-in-noise task and assessed whether cognitive reserve accumulated from long-term musical training bolsters or holds back age-related increase in neural activity. Older musicians exhibited less upregulation of task-induced functional connectivity than older non-musicians in auditory dorsal regions, which predicted better behavioral performance in older musicians. Furthermore, older musicians demonstrated more youth-like spatial patterns of functional connectivity, as compared to older non-musicians. Our findings show that cognitive reserve accrued through long-term music training holds back age-related neural recruitment during speech-in-noise perception and enlighten the intricate interplay between cognitive reserve and age-related upregulated activity during cognitive tasks.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.311
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2025
Admission routes2
Has abstractyes

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