Evidence map›Paper›PMID 35643845›Full record

ReviewTrends in cognitive sciences2022

Efficiently irrational: deciphering the riddle of human choice.

Paul W Glimcher

Erratum issuedAbstract readReview
In one paragraph

Review in Trends in cognitive sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Efficient numerosity estimation under limited time.PLoS computational biology · 2025
    Article
  8. Article
  9. Rational inattention in neural coding for economic choice.bioRxiv : the preprint server for biology · 2024
    Article
  10. Article
  11. Article
  12. Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  13. Article
  14. Article
  15. Nudging Strategies for Arable Land Protection Behavior in China.International journal of environmental research and public health · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Paul W GlimcherNeurosciences Institute, New York University Grossman School of Medicine, New York, NY 10016, USA. Electronic address: paulg@nyu.edu.

Funding

Neural Mechanisms of Cost and Benefit Integration During Decision-MakingR01DA038063 · NIDA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI GLIMCHER, PAUL W · 2014 to 2018
$1.7M
NIDA NIH HHS R01 DA038063
6 · The paper itself

Abstract

For the past half-century, cognitive and social scientists have struggled with the irrationalities of human choice behavior; people consistently make choices that are logically inconsistent. Is human choice behavior evolutionarily adaptive or is it an inefficient patchwork of competing mechanisms? In this review, I present an interdisciplinary synthesis arguing for a novel interpretation: choice is efficiently irrational. Connecting findings across disciplines suggests that observed choice behavior reflects a precise optimization of the trade-off between the costs of increasing the precision of the choice mechanism and the declining benefits that come as precision increases. Under these constraints, a rationally imprecise strategy emerges that works toward optimal efficiency rather than toward optimal rationality. This approach rationalizes many of the puzzling inconsistencies of human choice behavior, explaining why these inconsistencies arise as an optimizing solution in biological choosers.

Indexed as

Choice BehaviorDecision MakingCognitionHumansdecision-makingdivisive normalizationefficient codingsubjective valueutility

Identifiers

PMID35643845
PMCPMC9283329

What OpenQuestion holds

Textmetadata
LicenceTDM
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.