Evidence map›Paper›PMID 34878949›Full record

ArticlePsychological science2022

Attentional Guidance and Match Decisions Rely on Different Template Information During Visual Search.

Xinger Yu, Timothy D Hanks, Joy J Geng

Abstract read
In one paragraph

Article in Psychological science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Reappraising intuitions about consciousness.Frontiers in psychology · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Early Cortical Sensitivity and Speeded Target Selection Underlie Incidentally Learned Prioritization of Visual Features.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Expected distractor context biases the attentional template for target shapes.Journal of experimental psychology. Human perception and performance · 2023
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Attentional priority is determined by predicted feature distributions.Journal of experimental psychology. Human perception and performance · 2022
    Article
  20. Article
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

3 authors.

Xinger YuCenter for Mind and Brain, University of California, Davis.ORCID 0000-0002-9424-6348
Timothy D HanksCenter for Neuroscience, University of California, Davis.
Joy J GengCenter for Mind and Brain, University of California, Davis.ORCID 0000-0001-5663-9637

Funding

Quantifying the attentional templateR01MH113855 · NIMH · UNIVERSITY OF CALIFORNIA AT DAVIS · PI GENG, JOY JIA · 2018 to 2022
$1.9M
NIMH NIH HHS R01 MH113855
6 · The paper itself

Abstract

When searching for a target object, we engage in a continuous "look-identify" cycle in which we use known features of the target to guide attention toward potential targets and then to decide whether the selected object is indeed the target. Target information in memory (the target template or attentional template) is typically characterized as having a single, fixed source. However, debate has recently emerged over whether flexibility in the target template is relational or optimal. On the basis of evidence from two experiments using college students (

Indexed as

Memory, Short-TermVisual PerceptionAttentionDecision MakingHumansPattern Recognition, VisualReaction Timeattentiondrift-diffusion modelopen datatarget templatevisual search

Identifiers

PMID34878949
PMCPMC8822198

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.