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Record W4391388914 · doi:10.4103/jose.jose_7_22

Influence of auditory working memory in discriminating children with good musical abilities from children with poor musical abilities

2023· article· en· W4391388914 on OpenAlexaboutno aff
Sridhar Sampath, Devi Neelamegarajan

Bibliographic record

VenueJournal of All India Institute of Speech and Hearing · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
Fundersnot available
KeywordsMemory spanPsychologyMultivariate analysis of varianceAudiologyMusicalCognitionCognitive testWorking memoryTest (biology)Developmental psychologyPitch (Music)CorrelationCognitive psychologyPerceptionStatisticsMedicineMathematics

Abstract

fetched live from OpenAlex

Abstract Purpose: Musical abilities are associated with the perception of complex acoustic features in an auditory scene, which requires a good load of cognitive processing. Musical sleepers (individuals with good musical abilities without formal music training) were proven to be in adults, and their enhanced cognitive abilities were established, but such a phenomenon in children is not explored yet. Hence, the present study was carried out to assess auditory working memory (AWM) abilities in children with widespread musical abilities. Materials and Methods: Twenty-nine children within the age range of 7–13 years participated in the study. The children’s musical abilities were assessed using the Montreal Battery for Evaluation of Musical Abilities and scores were recorded. Sixteen and thirteen children were categorized into individuals with good and poor musical abilities, respectively, based on the 50th percentile score as the cutoff. The tests for AWM, such as forward span, backward span, and N-back, were administered. Results: Point biserial correlation showed that groups had a significant positive association with forward span ( r = 0.65; P = 0.00), backward span test ( r = 0.41; P = 0.02), and N-back test ( r = 0.70; P = 0.00). Multivariate analysis of variance (MANOVA) indicated a significant main effect of groups, and post hoc analysis showed that children with good musical abilities outperformed the ones with poor musical abilities in all three working memory measures. Further, Fisher’s discriminant analysis revealed that the N-back test, with discriminant coefficient of 0.75, is the best auditory-cognitive predictor of musical abilities in children. Conclusions: Children who had no musical training exhibited better musical ability. This may be mediated by improved AWM, but an additional investigation into the relationship between musical aptitude and other psychophysical abilities in children without musical training is necessary.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.265
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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