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Record W2132236475 · doi:10.1093/cercor/bhn082

Spatiotemporal Analysis of Auditory "What" and "Where" Working Memory

2008· article· en· W2132236475 on OpenAlexaff
Claude Alain, Kerrie L. McDonald, Nataša Žunić Kovačević, Anthony R. McIntosh

Bibliographic record

VenueCerebral Cortex · 2008
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsWorking memoryNeurosciencePsychologyAuditory cortexGyrusScalpFunctional magnetic resonance imagingBiologyAnatomyCognition

Abstract

fetched live from OpenAlex

Goal-directed attention to sound identity (what) and sound location (where) has been associated with increased neural activity in ventral and dorsal brain regions, respectively. In order to ascertain when such segregation occurs, we measured event-related potentials during an n-back (n = 1, 2) working memory task for sound identity or location, where stimuli selected randomly from 3 semantic categories (human, animal, music) were presented at 3 possible virtual locations. Accuracy and reaction times were comparable in both "what" and "where" tasks, albeit worse for the 2-back than for the 1-back condition. The partial least squares analysis of scalp-recorded and source waveform data revealed domain-specific activity beginning at about 200-ms poststimulus onset, which was best expressed as changes in source activity near Heschl's gyrus, and in central medial, occipital medial, right frontal and right parietal cortex. The effect of working memory load emerged at about 400-ms poststimulus and was expressed maximally over frontocentral scalp region and in sources located in the right temporal, frontal and parietal cortices. The results show that for identical sounds, top-down effects on processing "what" and "where" information is observable at about 200 ms after sound onset and involves a widely distributed neural network.

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 score0.549
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.266
Teacher spread0.226 · 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

Citations49
Published2008
Admission routes1
Has abstractyes

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