Evidence map›Paper›PMID 38443701›Full record

ArticleNature neuroscience2024

Population coding of strategic variables during foraging in freely moving macaques.

Neda Shahidi, Melissa Franch, Arun Parajuli, Paul Schrater, Anthony Wright, Xaq Pitkow, Valentin Dragoi

Open access · hybridAbstract read
In one paragraph

Article in Nature neuroscience, 2024. 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
5.1field-weighted citation impact, top 4% of its field
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, 21 citations in OpenAlex.

  1. Article
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  5. Primate neuroethology: a new synthesis.Trends in cognitive sciences · 2026
    Review
  6. Review
  7. Understanding the Brain as a Mentalizing Machine with a Symbol Grounding Function.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Review
  8. Article
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  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Generalizing from the Past, Choosing the Future.Perspectives on behavior science · 2020
    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

7 authors at 5 institutions in 2 countries.

Neda ShahidiDepartment of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, Houston, TX, USA.
Melissa FranchDepartment of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, Houston, TX, USA.
Arun ParajuliDepartment of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, Houston, TX, USA.
Paul SchraterDepartment of Computer Science, University of Minnesota, Minneapolis, MN, USA.
Anthony WrightDepartment of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, Houston, TX, USA.
Xaq Pitkow *Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA. xaq@cmu.edu.ORCID http://orcid.org/0000-0001-6376-329X
Valentin Dragoi *Department of Neurobiology and Anatomy, McGovern Medical School, University of Texas, Houston, Houston, TX, USA. vdragoi@rice.edu.ORCID http://orcid.org/0000-0002-9526-0926
The University of Texas Health Science Center at Houston · USBaylor College of Medicine · USGerman Primate Center · DERice University · USUniversity of Minnesota · US

Funding

Dynamic network computations for foraging in an uncertain environmentU01NS094368 · NINDS · BAYLOR COLLEGE OF MEDICINE · PI ANGELAKI, DORA, DRAGOI, VALENTIN · 2015 to 2017
$3.8M
NINDS NIH HHS U01 NS094368
6 · The paper itself

Abstract

Until now, it has been difficult to examine the neural bases of foraging in naturalistic environments because previous approaches have relied on restrained animals performing trial-based foraging tasks. Here we allowed unrestrained monkeys to freely interact with concurrent reward options while we wirelessly recorded population activity in the dorsolateral prefrontal cortex. The animals decided when and where to forage based on whether their prediction of reward was fulfilled or violated. This prediction was not solely based on a history of reward delivery, but also on the understanding that waiting longer improves the chance of reward. The task variables were continuously represented in a subspace of the high-dimensional population activity, and this compressed representation predicted the animal's subsequent choices better than the true task variables and as well as the raw neural activity. Our results indicate that monkeys' foraging strategies are based on a cortical model of reward dynamics as animals freely explore their environment.

Indexed as

Prefrontal CortexRewardAnimalsChoice BehaviorMacaca mulatta

Identifiers

PMID38443701
PMCPMC11001579
OpenAlexW4392460285

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.