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Record W2028339986 · doi:10.1037/a0038715

The influence of verbal and spatial working memory load on the time course of the Simon effect.

2015· article· en· W2028339986 on OpenAlexaff
Andrew Clouter, Ryan Wilson, Stefan Allen, Raymond M. Klein, Gail A. Eskes

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWorking memoryDistractionCognitive psychologyPsychologyStroop effectTask (project management)Simon effectAttentional controlControl (management)CognitionComputer scienceArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

The Simon effect refers to the relatively poorer response times and accuracy when responding to targets that appear in a task-irrelevant spatial location that is incongruent with the location of the correct response key, compared with targets that appear in spatially congruent locations. Like Stroop and flanker effects, the Simon effect is thought to result from conflict between an irrelevant response tendency and an intended response. Because attentional control has been linked to conflict resolution, the Simon task has been proffered as a possible tool for measuring the efficacy of executive control mechanisms. These mechanisms are also involved in working memory (WM) processes, and are thought to be responsible for maintaining information in the presence of continued processing or distraction. The present study investigated the interface between WM and attention by examining the time course of the Simon effect over the response time distributions under varying WM load conditions. Participants completed verbal 0-back, spatial 0-back, verbal 2-back, and spatial 2-back tasks. Results show that the Simon effect is diminished in high WM load tasks compared with low-load tasks, and that the Simon effect interacts with the spatial task domain such that the effect persists across the distribution of response times. In contrast, the Simon effect peaks and decays in verbal tasks. The results demonstrate that the Simon effect interacts with WM load and task domain. The results suggest that the effect is more modifiable than expected, and support a complex interface between WM and attentional control.

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)0.000
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 score0.416
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.088
GPT teacher head0.388
Teacher spread0.300 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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