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Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery

2015· article· en· W2398503190 on OpenAlexafffund
Takako Fujioka, Bernhard Roß, Laurel J. Trainor

Bibliographic record

VenueJournal of Neuroscience · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcMaster UniversityUniversity of TorontoOntario Institute for Cancer Research
FundersCanadian Institutes of Health Research
KeywordsMetronomeMagnetoencephalographyBeat (acoustics)WaltzRhythmStimulus (psychology)PsychologyAudiologyPerceptionCommunicationElectroencephalographyNeuroscienceSpeech recognitionCognitive psychologyAcousticsComputer sciencePhysicsMedicine

Abstract

fetched live from OpenAlex

Dancing to music involves synchronized movements, which can be at the basic beat level or higher hierarchical metrical levels, as in a march (groups of two basic beats, one-two-one-two …) or waltz (groups of three basic beats, one-two-three-one-two-three …). Our previous human magnetoencephalography studies revealed that the subjective sense of meter influences auditory evoked responses phase locked to the stimulus. Moreover, the timing of metronome clicks was represented in periodic modulation of induced (non-phase locked) β-band (13-30 Hz) oscillation in bilateral auditory and sensorimotor cortices. Here, we further examine whether acoustically accented and subjectively imagined metric processing in march and waltz contexts during listening to isochronous beats were reflected in neuromagnetic β-band activity recorded from young adult musicians. First, we replicated previous findings of beat-related β-power decrease at 200 ms after the beat followed by a predictive increase toward the onset of the next beat. Second, we showed that the β decrease was significantly influenced by the metrical structure, as reflected by differences across beat type for both perception and imagery conditions. Specifically, the β-power decrease associated with imagined downbeats (the count "one") was larger than that for both the upbeat (preceding the count "one") in the march, and for the middle beat in the waltz. Moreover, beamformer source analysis for the whole brain volume revealed that the metric contrasts involved auditory and sensorimotor cortices; frontal, parietal, and inferior temporal lobes; and cerebellum. We suggest that the observed β-band activities reflect a translation of timing information to auditory-motor coordination. SIGNIFICANCE STATEMENT: With magnetoencephalography, we examined β-band oscillatory activities around 20 Hz while participants listened to metronome beats and imagined musical meters such as a march and waltz. We demonstrated that β-band event-related desynchronization in the auditory cortex differentiates between beat positions, specifically between downbeats and the following beat. This is the first demonstration of β-band oscillations related to hierarchical and internalized timing information. Moreover, the meter representation in the β oscillations was widespread across the brain, including sensorimotor and premotor cortices, parietal lobe, and cerebellum. The results extend current understanding of the role of β oscillations in neural processing of predictive timing.

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 score0.005

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 head0.115
GPT teacher head0.335
Teacher spread0.220 · 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".

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Citations244
Published2015
Admission routes2
Has abstractyes

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