Evidence map›Paper›PMID 30297430›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Humans incorporate attention-dependent uncertainty into perceptual decisions and confidence.

Rachel N Denison, William T Adler, Marisa Carrasco, Wei Ji Ma

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Computational and Neuronal Basis of Visual Confidence.Annual review of vision science · 2025
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Challenging the Bayesian confidence hypothesis in perceptual decision-making.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. The future of metacognition research: Balancing construct breadth with measurement rigor.Cortex; a journal devoted to the study of the nervous system and behavior · 2024
    Review
  20. Think twice: Re-assessing confidence improves visual metacognition.Attention, perception & psychophysics · 2024
    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

4 authors.

Rachel N DenisonDepartment of Psychology, New York University, New York, NY 10003; rachel.denison@nyu.edu.ORCID 0000-0002-6304-5236
William T AdlerCenter for Neural Science, New York University, New York, NY 10003.ORCID 0000-0003-4720-7861
Marisa CarrascoDepartment of Psychology, New York University, New York, NY 10003.
Wei Ji MaDepartment of Psychology, New York University, New York, NY 10003.

Funding

Vision Core Grant- Design and Fabrication ModuleP30EY013079 · NEI · NEW YORK UNIVERSITY · PI MOVSHON, J ANTHONY · 2000 to 2025
$14.2M
TRAINING IN VISUAL NEUROSCIENCET32EY007136 · NEI · NEW YORK UNIVERSITY · PI J ANTHONY MOVSHON · 1993 to 2026
$5.3M
Dynamics of Temporal AttentionF32EY025533 · NEI · NEW YORK UNIVERSITY · PI DENISON, RACHEL · 2016 to 2017
$116k
NEI NIH HHS F32 EY025533NEI NIH HHS P30 EY013079NEI NIH HHS T32 EY007136
6 · The paper itself

Abstract

Perceptual decisions are better when they take uncertainty into account. Uncertainty arises not only from the properties of sensory input but also from cognitive sources, such as different levels of attention. However, it is unknown whether humans appropriately adjust for such cognitive sources of uncertainty during perceptual decision-making. Here we show that, in a task in which uncertainty is relevant for performance, human categorization and confidence decisions take into account uncertainty related to attention. We manipulated uncertainty in an orientation categorization task from trial to trial using only an attentional cue. The categorization task was designed to disambiguate decision rules that did or did not depend on attention. Using formal model comparison to evaluate decision behavior, we found that category and confidence decision boundaries shifted as a function of attention in an approximately Bayesian fashion. This means that the observer's attentional state on each trial contributed probabilistically to the decision computation. This responsiveness of an observer's decisions to attention-dependent uncertainty should improve perceptual decisions in natural vision, in which attention is unevenly distributed across a scene.

Indexed as

AttentionBayes TheoremCognitionDecision MakingFemaleHumansMaleOrientationTask Performance and AnalysisUncertaintyVisual PerceptionattentionBayesianconfidencecriterionperceptual decision

Identifiers

PMID30297430
PMCPMC6205425

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.