Evidence map›Paper›PMID 42669730›Full record

ArticleNature communications2026

Foraging models explain human exploration in uncertain tasks.

Meriam Zid, Veldon-James Laurie, Jorge Ramírez-Ruiz, Alix Lavigne-Champagne, Akram Shourkeshti, Dameon C Harrell, Alexander B Herman, R Becket Ebitz

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Meriam ZidDepartment of Neuroscience, University of Montreal, Montreal, QC, Canada. meriam.zid@umontreal.ca.ORCID 0009-0002-7957-4789
Veldon-James LaurieDepartment of Neuroscience, University of Montreal, Montreal, QC, Canada.ORCID 0009-0007-4975-0055
Jorge Ramírez-RuizDepartment of Neuroscience, University of Montreal, Montreal, QC, Canada.ORCID 0000-0002-3505-3319
Alix Lavigne-ChampagneDepartment of Neuroscience, University of Montreal, Montreal, QC, Canada.ORCID 0009-0003-7893-3900
Akram ShourkeshtiDepartment of Neuroscience, University of Montreal, Montreal, QC, Canada.
Dameon C HarrellDepartment of Psychiatry, University of Minnesota, Minneapolis, MN, USA.
Alexander B Herman *Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA. herma686@umn.edu.ORCID 0000-0001-6229-433X
R Becket Ebitz *Department of Neuroscience, University of Montreal, Montreal, QC, Canada. rebitz@gmail.com.ORCID 0000-0001-5412-9502

Funding

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (NSERC Canadian Network for Research and Innovation in Machining Technology) RGPIN-2020-05577
6 · The paper itself

Abstract

Different fields have fundamentally different models of how decisions are made. Psychology and neuroscience tend to assume that decisions are made by calculating and comparing the values of all options. In ethology, conversely, decisions tend to be binary regardless of the number of options: Decision-makers calculate the value of continuing to exploit some option and explore only when this value drops below a threshold. Because these fields use incompatible methods, it remains unclear which view better describes human decision-making. We find that humans use compare-to-threshold computations even in classic compare-alternative tasks. Because the reinforcement-learning models typically used in the cognitive and brain sciences depend on compare-alternative computations, we also develop a compare-to-threshold foraging model. Compared to previous models, the foraging model better fits participant behavior, predicts the tendency to repeat choices, and predicts held-out participants that were almost impossible under traditional compare-alternative models. These results suggest that humans use compare-to-threshold computations in more environments than were previously known.

Indexed as

Decision MakingExploratory BehaviorModels, PsychologicalAdultChoice BehaviorFemaleHumansMaleReinforcement Machine LearningUncertainty

Identifiers

PMID42669730
PMCPMC13526786

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.