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Record W1897362985 · doi:10.1093/cercor/bhp201

Temporal Dynamics of Selective Attention during Dichotic Listening

2009· article· en· W1897362985 on OpenAlexafffund

Bibliographic record

VenueCerebral Cortex · 2009
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsDichotic listeningAudiologyStimulus (psychology)PsychologyMagnetoencephalographyBinaural recordingSelective attentionMonauralSelective auditory attentionActive listeningAcousticsCommunicationElectroencephalographyCognitive psychologyMedicineNeuroscienceCognitionPhysics

Abstract

fetched live from OpenAlex

The ability to selectively attend to one sound and ignore other competing sounds is essential for auditory communication. Subjects in our study detected occasional changes in the frequency of amplitude modulation in sounds presented to one ear while ignoring sounds in the other ear. Neuromagnetic source analysis revealed attention-related activity in a cortical network including primary auditory cortices, posterior superior temporal gyri, inferior parietal lobules (IPLs), inferior frontal gyri (IFG), and medial frontal gyri. Time courses of event-related magnetoencephalography responses were analyzed during the interval between stimulus presentation and behavioral response. Enhanced neural responses to targets and standards in the attended ear indicated early modulation of sensitivity in the attended sensory channel. A subsequent process of discriminative stimulus selection was indexed by a response increase over time for targets and decreasing activity for standards. Enhanced responses to deviants in the unattended ear indicated discriminative processing of unattended inputs as well, though to a lesser extent than for attended stimuli. Superior temporal gyrus, planum temporale, and the IPL were prominently involved in stimulus selection, whereas medial frontal regions were linked to initiation of behavioral responses and sustained activity in IFG suggested a role in attentional control.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.935
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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 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

Citations2
Published2009
Admission routes2
Has abstractyes

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