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Record W4288078444 · doi:10.1177/20592043221109958

The Neural Basis of Tonal Processing in Music: An ALE Meta-Analysis

2022· article· en· W4288078444 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMusic & Science · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcMaster University
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsFunctional magnetic resonance imagingPsychologyCognitive psychologyInsulaMagnetoencephalographyCognitive scienceElectroencephalographyNeuroscience

Abstract

fetched live from OpenAlex

Music is used as an important medium for communication in human societies, often times to enhance the emotional meaning of narrative scenarios and ritual events. Music has a number of domain-specific tonal devices for doing this, spanning from scale structure to harmonic progressions and beyond. In order to explore the neural basis of tonal processing in music, we carried out an activation likelihood estimation (ALE) meta-analysis of 20 published functional magnetic resonance imaging studies of tonal cognition, with an emphasis on harmony processing. The most concordant areas of activation across these studies occurred at the junction of the inferior frontal gyrus, anterior insula, and orbitofrontal cortex in Brodmann areas 47 and 13 in the right hemisphere. This region is associated not only with emotion in general, but with the conveyance of affective meanings during communication processes, including speech prosody and music.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.766
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.009
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.189
GPT teacher head0.340
Teacher spread0.151 · 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