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Record W2006040313 · doi:10.1167/8.16.13

Visuospatial experience modulates attentional capture: Evidence from action video game players

2008· article· en· W2006040313 on OpenAlexafffund
Greg L. West, Sara Stevens, Carson Pun, Jay Pratt

Bibliographic record

VenueJournal of Vision · 2008
Typearticle
Languageen
FieldComputer Science
TopicVisual Attention and Saliency Detection
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVideo gameAction (physics)SalientSensory systemPsychologyTask (project management)Sensory processingCognitive psychologyVisual processingCognitionNeuroscienceComputer sciencePerceptionMultimediaArtificial intelligence

Abstract

fetched live from OpenAlex

Visuospatial experience, the prolonged engagement in a demanding visual task, obtained through action video game play enhances several visual and cognitive processes. The underlying mechanisms involved in these processes, however, remain unclear. Here we demonstrate that experience with action video games modulates early sensory processing, resulting in increases sensitivity to salient visual events that capture attention. In two experiments, we show using a Temporal Order Judgment (TOJ) and a Signal Detection Paradigm (d') that action video game players show greater sensitivity to exogenous sensory events in the visual array. These results suggest that visuospatial experience modulates the earliest sensory aspects of visual processing.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.054
GPT teacher head0.336
Teacher spread0.282 · 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 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

Citations146
Published2008
Admission routes2
Has abstractyes

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