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Record W2119114863 · doi:10.1162/jocn.2009.21042

Inhibition of Return in the Covert Deployment of Attention: Evidence from Human Electrophysiology

2008· article· en· W2119114863 on OpenAlexaff
John J. McDonald, Clayton Hickey, Jessica J. Green, Jennifer C. Whitman

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsN2pcCovertInhibition of returnPsychologyVisual searchTask (project management)Perspective (graphical)Cognitive psychologyNeuroscienceElectrophysiologySoftware deploymentVisual attentionCognitionComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

People are slow to react to objects that appear at recently attended locations. This delay-known as inhibition of return (IOR)-is believed to aid search of the visual environment by discouraging inspection of recently inspected objects. However, after two decades of research, there is no evidence that IOR reflects an inhibition in the covert deployment of attention. Here, observers participated in a modified visual-search task that enabled us to measure IOR and an ERP component called the posterior contralateral N2 (N2pc) that reflects the covert deployment of attention. The N2pc was smaller when a target appeared at a recently attended location than when it appeared at a recently unattended location. This reduction was due to modulation of neural processing in the visual cortex and the right parietal lobe. Importantly, there was no evidence for a delay in the N2pc. We conclude that in our task, the inhibitory processes underlying IOR reduce the probability of shifting attention to recently attended locations but do not delay the covert deployment of attention itself.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.207
GPT teacher head0.391
Teacher spread0.184 · 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

Citations54
Published2008
Admission routes1
Has abstractyes

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