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Conditional Associative Memory for Musical Stimuli in Nonmusicians: Implications for Absolute Pitch

2005· article· en· W1974648765 on OpenAlexafffund
Patrick Bermudez, Robert J. Zatorre

Bibliographic record

VenueJournal of Neuroscience · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health Research
KeywordsDorsolateral prefrontal cortexPsychologyPrefrontal cortexAssociative propertyWorking memoryFunctional magnetic resonance imagingNeuroscienceCognitive psychologyPosterior parietal cortexAudiologyCognitionMathematicsMedicine

Abstract

fetched live from OpenAlex

A previous positron emission tomography (PET) study of musicians with and without absolute pitch put forth the hypothesis that the posterior dorsolateral prefrontal cortex is involved in the conditional associative aspect of the identification of a pitch. In the work presented here, we tested this hypothesis by training eight nonmusicians to associate each of four different complex musical sounds (triad chords) with an arbitrary number in a task designed to have limited analogy to absolute-pitch identification. Each subject under-went a functional magnetic resonance imaging scanning procedure both before and after training. Active condition (identification of chords)-control condition (amplitude-matched noise bursts) comparisons for the pretraining scan showed no significant activation maxima. The same comparison for the posttraining scan revealed significant peaks of activation in posterior dorsolateral prefrontal, ventrolateral prefrontal, and parietal areas. A conjunction analysis was performed to show that the posterior dorsolateral prefrontal activity in this study is similar to that observed in the aforementioned PET study. We conclude that the posterior dorsolateral prefrontal cortex is selectively involved in the conditional association aspect of our task, as it is in the attribution of a verbal label to a note by absolute-pitch musicians.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.920
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.107
GPT teacher head0.374
Teacher spread0.267 · 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

Citations61
Published2005
Admission routes2
Has abstractyes

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