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Record W2140038153 · doi:10.1093/cercor/bhg089

Human Auditory Cortical Dynamics During Perception of Long Acoustic Sequences: Phase Tracking of Carrier Frequency by the Auditory Steady-state Response

2003· article· en· W2140038153 on OpenAlexfundno aff
Aniruddh P. Patel

Bibliographic record

VenueCerebral Cortex · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
FundersJohn Jay College of Criminal JusticeMcGill UniversityJohns Hopkins University
KeywordsAuditory cortexPerceptionSteady state (chemistry)Auditory perceptionAuditory scene analysisDynamics (music)PsychologyAudiologyAcousticsNeurosciencePhysicsMedicineChemistry

Abstract

fetched live from OpenAlex

We recorded human auditory cortical activity during the perception of long, changing acoustic signals and analyzed information provided by dynamic neural population measures over a large range of time intervals (approximately 24 ms-5 s). Participants listened to musical scales that were amplitude modulated at a rate of 41.5 Hz, generating an ongoing, stimulus-related oscillatory brain signal, the auditory steady-state response (aSSR). The aSSR generated energy at the amplitude modulation rate that was recorded using magnetoencephalography. As in previous work, the timing (phase) of this response varied with stimulus carrier frequency over the entire course of minute-long tone sequences ('phase tracking' of carrier frequency). The length of the time interval over which phase was calculated was systematically varied; significant phase tracking was regularly observed at analysis intervals of <50 ms in length. The right auditory cortex exhibited better phase tracking performance than the left at analysis intervals of 24-240 ms, and frequency dependent phase delays were consistently larger than those predicted by cochlear mechanics. Based on these empirical data, a model of the neural populations responsible for phase tracking suggests that it is produced by a subpopulation ( approximately 25%) of the cells generating the aSSR.

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)0.001
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 score0.541
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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

Citations24
Published2003
Admission routes1
Has abstractyes

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