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Record W4318174426 · doi:10.1093/cercor/bhac517

Absolute pitch: neurophysiological evidence for early brain activity in prefrontal cortex

2022· article· en· W4318174426 on OpenAlexaff
Vivek Sharma, Michael H. Thaut, Frank Russo, Claude Alain

Bibliographic record

VenueCerebral Cortex · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsBaycrest HospitalToronto Metropolitan UniversityUniversity of TorontoSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsNeurophysiologyPrefrontal cortexNeurosciencePsychologyBrain activity and meditationElectroencephalographyCognition

Abstract

fetched live from OpenAlex

Absolute pitch (AP) is the ability to rapidly label pitch without an external reference. The speed of AP labeling may be related to faster sensory processing. We compared time needed for auditory processing in AP musicians, non-AP musicians, and nonmusicians (NM) using high-density electroencephalographic recording. Participants responded to pure tones and sung voice. Stimuli evoked a negative deflection peaking at ~100 ms (N1) post-stimulus onset, followed by a positive deflection peaking at ~200 ms (P2). N1 latency was shortest in AP, intermediate in non-AP musicians, and longest in NM. Source analyses showed decreased auditory cortex and increased frontal cortex contributions to N1 for complex tones compared with pure tones. Compared with NM, AP musicians had weaker source currents in left auditory cortex but stronger currents in left inferior frontal gyrus (IFG) during N1, and stronger currents in left IFG during P2. Compared with non-AP musicians, AP musicians exhibited stronger source currents in right insula and left IFG during N1, and stronger currents in left IFG during P2. Non-AP musicians had stronger N1 currents in right auditory cortex than nonmusicians. Currents in left IFG and left auditory cortex were correlated to response times exclusively in AP. Findings suggest a left frontotemporal network supports rapid pitch labeling in AP.

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)0.001
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 score0.988
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.119
GPT teacher head0.331
Teacher spread0.213 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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