Evidence map›Paper›PMID 36326648›Full record

ArticleJournal of experimental psychology. Learning, memory, and cognition2024

Selection history and the strategic control of attention.

Andy J Kim, David S Lee, James D Grindell, Brian A Anderson

Abstract read
In one paragraph

Article in Journal of experimental psychology. Learning, memory, and cognition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Andy J KimDepartment of Psychological and Brain Sciences, Texas A&M University.ORCID 0000-0003-1124-0213
David S LeeDepartment of Psychological and Brain Sciences, Texas A&M University.
James D GrindellDepartment of Psychological and Brain Sciences, Texas A&M University.
Brian A AndersonDepartment of Psychological and Brain Sciences, Texas A&M University.

Funding

The Control of Attention and Learning from Physical EffortR01DA046410 · NIDA · TEXAS A&M UNIVERSITY · PI ANDERSON, BRIAN AUGUST · 2019 to 2023
$1.9M
NIDA NIH HHS R01 DA046410NIH HHS
6 · The paper itself

Abstract

Attention is biased toward features aligning with task goals and stimuli previously allocated attentional priority (selection history). The relationship between selection history and the strategic control of attention has scarcely been explored. In the present study, we utilized a modified version of the Adaptive Choice Visual Search (ACVS) task to determine whether the choice of visual search strategy varies with the strategies participants have elected to use in the past. Participants were tasked with searching through stimuli presented in two task-relevant colors on each trial to find one of two targets. The distribution of stimuli rendered in these two colors was manipulated between subjects, with one group receiving more imbalanced displays during learning. Participants who experienced the more imbalanced displays quickly learned the optimal visual search strategy of searching through the less abundant color, which maximized performance. Critically, these participants retained their tendency toward this learned strategy in a subsequent test phase in which displays were less imbalanced, in contrast to participants who completed the same test phase but had only experienced the less imbalanced displays. Our results demonstrate that, without explicit instruction, the choice of visual search strategy is to some degree dependent upon selection history. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Indexed as

AttentionLearningHumansReaction Time

Identifiers

PMID36326648
PMCPMC10319403

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.