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Beta and Gamma Rhythms in Human Auditory Cortex during Musical Beat Processing

2009· article· en· W2013419815 on OpenAlexafffund
Takako Fujioka, Laurel J. Trainor, Edward W. Large, Bernhard Roß

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsBaycrest HospitalMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMagnetoencephalographyRhythmAuditory cortexBeat (acoustics)Stimulus (psychology)NeuroscienceBeta RhythmAudiologyPsychologyActive listeningBETA (programming language)CommunicationElectroencephalographyPhysicsCognitive psychologyMedicineAcousticsComputer science

Abstract

fetched live from OpenAlex

We examined beta- (approximately 20 Hz) and gamma- (approximately 40 Hz) band activity in auditory cortices by means of magnetoencephalography (MEG) during passive listening to a regular musical beat with occasional omission of single tones. The beta activity decreased after each tone, followed by an increase, thus forming a periodic modulation synchronized with the stimulus. The beta decrease was absent after omissions. In contrast, gamma-band activity showed a peak after tone and omission, suggesting underlying endogenous anticipatory processes. We propose that auditory beta and gamma oscillations have different roles in musical beat encoding and auditory-motor interaction.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.107
GPT teacher head0.354
Teacher spread0.247 · 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

Citations272
Published2009
Admission routes2
Has abstractyes

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