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Record W3197617734 · doi:10.1167/jov.21.9.2307

Latent attentional capture is dependent on search display duration

2021· article· en· W3197617734 on OpenAlexaff
Annie K. Truuvert, Matthew D. Hilchey, Susanne Ferber, Jay Pratt

Bibliographic record

VenueJournal of Vision · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStimulus (psychology)Visual searchPsychologyVisual attentionCognitive psychologyCapture effectLatent inhibitionComputer sciencePerceptionNeuroscienceClassical conditioning

Abstract

fetched live from OpenAlex

While research from additional singleton paradigms suggest that a uniquely transient visual stimulus reliably captures visuospatial attention, research from contingent capture paradigms suggest capture by such a stimulus occurs only when it shares features of the target. Gaspelin, Ruthruff, and Lien (2016) proposed a solution to this discrepancy: attentional capture by a uniquely transient visual stimulus may be latent in contingent capture paradigms when the target in the subsequent search array is easily distinguished from distractors. That is, capture effects are not seen when attention does not need to dwell for long on the onset cue location to reject distractors because they are easily distinguishable from the target. Capture effects are revealed, however, in difficult visual search tasks because attention must dwell on the onset cue location because of high target-distractor similarity. It remains unclear why attention capture effects from an abrupt onset have been reliably observed in cueing studies, regardless of whether visual distractors are included in the target display. To examine this, our first experiment embedded a distractor-less search condition into an otherwise standard contingent capture paradigm to evaluate whether latent capture could also be revealed by merely removing the distractors. Consistent with the attentional dwelling account, we found latent cueing effects in the distractor-less condition. Our second experiment was identical to the first except the search array duration was extended from 120 ms to until response, as is typical of more traditional Posner cueing paradigms that show capture from a uniquely transient visual stimulus. This experiment revealed similar capture effects across all levels of search difficulty, consistent with more traditional Posner cueing paradigms but inconsistent with Gaspelin et al (2016). The results suggest that attentional capture from cues that do not share features with targets can be moderated by target display duration.

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)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.126
GPT teacher head0.413
Teacher spread0.287 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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