Evidence map›Paper›PMID 33361819›Full record

ArticleNature2021

Evolving schema representations in orbitofrontal ensembles during learning.

Jingfeng Zhou, Chunying Jia, Marlian Montesinos-Cartagena, Matthew P H Gardner, Wenhui Zong, Geoffrey Schoenbaum

Open access · greenAbstract read
In one paragraph

Article in Nature, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
8.6field-weighted citation impact, top 1% 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

73 citing papers in PubMed, 146 citations in OpenAlex.

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  13. Beyond ensemble averages: single-entity approaches for complex systems.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2026
    Review
  14. Article
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  19. Article
  20. Orbitofrontal-Hippocampal State Coding Dynamics during Reversal Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article

13 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Jingfeng ZhouIntramural Research Program of the National Institute on Drug Abuse, Baltimore, MD, USA. jingfeng.zhou@nih.gov.
Chunying JiaDepartment of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA.
Marlian Montesinos-CartagenaIntramural Research Program of the National Institute on Drug Abuse, Baltimore, MD, USA.
Matthew P H GardnerIntramural Research Program of the National Institute on Drug Abuse, Baltimore, MD, USA.
Wenhui ZongIntramural Research Program of the National Institute on Drug Abuse, Baltimore, MD, USA.
Geoffrey SchoenbaumIntramural Research Program of the National Institute on Drug Abuse, Baltimore, MD, USA. geoffrey.schoenbaum@nih.gov.
National Institute on Drug Abuse · USUniversity of Maryland, Baltimore County · US

Funding

Associative learning, decision-making, and addictionZIADA000587 · NIDA · NATIONAL INSTITUTE ON DRUG ABUSE · PI SCHOENBAUM, GEOFFREY · 2012 to 2025
$47.7M
Intramural NIH HHS ZIA DA000587NIDA K99DA049888
6 · The paper itself

Abstract

How do we learn about what to learn about? Specifically, how do the neural elements in our brain generalize what has been learned in one situation to recognize the common structure of-and speed learning in-other, similar situations? We know this happens because we become better at solving new problems-learning and deploying schemas

Indexed as

Models, NeurologicalAccelerationAnimalsCognitionLearningLogicMaleNeuronsOdorantsPrefrontal CortexRatsRats, Long-EvansReward

Identifiers

PMID33361819
PMCPMC7906913
OpenAlexW3117063919

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.