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Record W4323804505 · doi:10.1093/cercor/bhad034

Enhanced neural mechanisms of set shifting in musically trained adolescents and young adults: converging fMRI, EEG, and behavioral evidence

2023· article· en· W4323804505 on OpenAlexaff
Katri Saarikivi, T.M. Vanessa Chan, Minna Huotilainen, Mari Tervaniemi, Vesa Putkinen

Bibliographic record

VenueCerebral Cortex · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversity of Toronto
FundersJenny ja Antti Wihurin RahastoAcademy of Finland
KeywordsPsychologyNeural correlates of consciousnessSet (abstract data type)P3bTask (project management)Executive functionsAudiologyElectroencephalographyScalpWorking memoryCognitive psychologyEvent-related potentialDevelopmental psychologyNeuroscienceCognitionMedicineComputer science

Abstract

fetched live from OpenAlex

Musically trained individuals have been found to outperform untrained peers in various tasks for executive functions. Here, we present longitudinal behavioral results and cross-sectional, event-related potential (ERP), and fMRI results on the maturation of executive functions in musically trained and untrained children and adolescents. The results indicate that in school-age, the musically trained children performed faster in a test for set shifting, but by late adolescence, these group differences had virtually disappeared. However, in the fMRI experiment, the musically trained adolescents showed less activity in frontal, parietal, and occipital areas of the dorsal attention network and the cerebellum during the set-shifting task than untrained peers. Also, the P3b responses of musically trained participants to incongruent target stimuli in a task for set shifting showed a more posterior scalp distribution than control group participants' responses. Together these results suggest that the musician advantage in executive functions is more pronounced at an earlier age than in late adolescence. However, it is still reflected as more efficient recruitment of neural resources in set-shifting tasks, and distinct scalp topography of ERPs related to updating and working memory after childhood.

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 score0.913
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.282
Teacher spread0.245 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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