Evidence map›Paper›PMID 30804531›Full record

ReviewNature neuroscience2019

Optimality and heuristics in perceptual neuroscience.

Justin L Gardner

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Decoupling Choice from Motor Response Reduces Choice-History Effects.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
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  4. Review
  5. Review
  6. Sensory choices as logistic classification.bioRxiv : the preprint server for biology · 2024
    Article
  7. Article
  8. Article
  9. Article
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  12. Beyond ℓ1 sparse coding in V1.PLoS computational biology · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Rational inattention in mice.Science advances · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Justin L GardnerDepartment of Psychology, Stanford University, Stanford, California, USA. jlg@stanford.edu.ORCID http://orcid.org/0000-0003-2220-5050

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The foundation for modern understanding of how we make perceptual decisions about what we see or where to look comes from considering the optimal way to perform these behaviors. While statistical computation is useful for deriving the optimal solution to a perceptual problem, optimality requires perfect knowledge of priors and often complex computation. Accumulating evidence, however, suggests that optimal perceptual goals can be achieved or approximated more simply by human observers using heuristic approaches. Perceptual neuroscientists captivated by optimal explanations of sensory behaviors will fail in their search for the neural circuits and cortical processes that implement an optimal computation whenever that behavior is actually achieved through heuristics. This article provides a cross-disciplinary review of decision-making with the aim of building perceptual theory that uses optimality to set the computational goals for perceptual behavior but, through consideration of ecological, computational, and energetic constraints, incorporates how these optimal goals can be achieved through heuristic approximation.

Indexed as

AnimalsBrainDecision MakingGoalsHeuristicsHumansModels, PsychologicalPerceptionSignal Detection, Psychological

Identifiers

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.