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Record W2042900297 · doi:10.1167/10.7.224

How Does Reflexive Visuospatial Attention Speed Target Processing?

2010· article· en· W2042900297 on OpenAlexaff
Naseem Al-Aidroos, Marco Adamo, Joyce Tam, Susanne Ferber, Jay Pratt

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCued speechPsychologyPerceptionCognitive psychologyVisual processingN2pcVisual searchVisual attentionNeuroscience

Abstract

fetched live from OpenAlex

Irrelevant transient stimuli can speed responses to visual targets that appear soon after at the same location (relative to other locations). How do these stimuli speed target processing? Traditionally, they are thought to act as cues that reflexively capture visuospatial attention, a mechanism that provides processing priority to specific regions of the visual field. Here we report behavioral and electrophysiological evidence of the limits of this explanation. In the first experiment we show that while targets are identified faster at a cues locations (the classic cueing effect), this effect is increased when the cue and target are visually similar. Thus, the reflexive cueing effect is not a general attentional enhancement of all visual processing within a region of space; rather, some component of the effect is related to the identity of the cue. In a second experiment we used attentional control settings to manipulate whether cues captured attention or not and measured event-related potentials. Cues that captured attention produced a posterior contralateral positivity between 200 to 400 ms after their onset that was absent when they did not capture attention. This component resembles the Ptc, which has been associated with the resolution of perceptual competition between proximal stimuli. More importantly, a similar component was observed time-locked to the target onset, except when the target appeared at a cued location. Thus cues may speed target processing by inducing competition resolution, making this process unnecessary when the target subsequently appears at that location. These results do not fit well with the notion that reflexive attention is a mechanism deployed to enhance visual processing within regions of space. Instead, the present results suggest that transient stimuli initiate perceptual processing, and subsequent targets can exploit these ongoing processes if, for example, they appear at the same location or are visually similar.

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)0.004
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.358
Teacher spread0.326 · 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
Published2010
Admission routes1
Has abstractyes

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