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Record W2999813904 · doi:10.3758/s13423-019-01692-9

A critical review of the cognitive and perceptual factors influencing attentional scaling and visual processing

2020· review· en· W2999813904 on OpenAlexaff
Rebecca K. Lawrence, Mark Edwards, Louisa A. Talipski, Stephanie C. Goodhew

Bibliographic record

VenuePsychonomic Bulletin & Review · 2020
Typereview
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Toronto
FundersAustralian Research CouncilAustralian Government
KeywordsPsychologyCognitive psychologyCognitionPerceptionProcess (computing)Gaze-contingency paradigmVisual attentionAttentional blinkAttentional controlScalingInformation processingVisual perceptionVisual fieldCognitive scienceNeuroscienceComputer science

Abstract

fetched live from OpenAlex

An important mechanism used to selectively process relevant information in the environment is spatial attention. One fundamental way in which spatial attention is deployed is attentional scaling - the process of focusing attentional resources either narrowly or broadly across the visual field. Although early empirical work suggested that narrowing attention improves all aspects of visual processing, recent studies have demonstrated that narrowing attention can also have no effect or even a detrimental impact when it comes to vision that is thought to be mediated via the magnocellular pathway of the visual system. Here, for the first time, we synthesize empirical evidence measuring the behavioral effects of attentional scaling on tasks gauging the contribution of the major neural pathways of the visual system, with the purpose of determining the potential factors driving these contradictory empirical findings. This analysis revealed that attentional scaling could be best understood by considering the unique methodologies used in the research literature to date. The implications of this analysis for theoretical frameworks of attentional scaling are discussed, and methodological improvements for future research are proposed.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.410
Teacher spread0.290 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations19
Published2020
Admission routes1
Has abstractno

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