Evidence map›Paper›PMID 37957318›Full record

ArticleNature neuroscience2023

Meta-reinforcement learning via orbitofrontal cortex.

Ryoma Hattori, Nathan G Hedrick, Anant Jain, Shuqi Chen, Hanjia You, Mariko Hattori, Jun-Hyeok Choi, Byung Kook Lim, Ryohei Yasuda, Takaki Komiyama

Erratum issuedAbstract read
In one paragraph

Article in Nature neuroscience, 2023. 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 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Orbitofrontal noradrenaline supports adaptive learning-rate adjustment in probabilistic reversal learning.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Meta-learning is expressed through altered prefrontal cortical dynamics.bioRxiv : the preprint server for biology · 2026
    Article
  10. Mesocorticostriatal Reinforcement Learning of State Representation and Value with Implications for the Mechanisms of Schizophrenia.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  11. Article
  12. Cell-type-specific sustained value representations in the claustrum.bioRxiv : the preprint server for biology · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ryoma HattoriDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA. rhattori0204@gmail.com.ORCID 0000-0002-4908-4933
Nathan G HedrickDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0003-3933-7033
Anant JainMax Planck Florida Institute for Neuroscience, Jupiter, FL, USA.
Shuqi ChenDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0001-5976-3940
Hanjia YouDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA.ORCID 0009-0008-4820-229X
Mariko HattoriDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA.
Jun-Hyeok ChoiDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA.
Byung Kook LimDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-3766-5415
Ryohei YasudaMax Planck Florida Institute for Neuroscience, Jupiter, FL, USA.ORCID 0000-0001-6263-9297
Takaki KomiyamaDepartment of Neurobiology, University of California San Diego, La Jolla, CA, USA. tkomiyama@ucsd.edu.ORCID 0000-0001-9609-4600

Funding

Vision BiostatisticsP30EY022589 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LINDA M ZANGWILL · 2012 to 2026
$10.3M
Neuronal Intracellular Signaling Underlying Synaptic, Circuit and Behavioral PlasticityR35NS116804 · NINDS · MAX PLANCK FLORIDA CORPORATION · PI Ryohei Yasuda · 2020 to 2026
$7.8M
Mechanisms of Ras Signaling in Single SynapsesR01MH080047 · NIMH · MAX PLANCK FLORIDA CORPORATION · PI YASUDA, RYOHEI · 2007 to 2023
$6.8M
Cortical Control of Motor LearningR01NS091010 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2015 to 2024
$3.7M
Cortical plasticity during reinforcement learning - Diversity SupplementR01MH128746 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Takaki Komiyama · 2022 to 2026
$2.3M
Context-dependent plasticity of adult-born neuronsR01DC018545 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2020 to 2024
$2.2M
Experience-driven plasticity of visual circuitsR01EY025349 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2015 to 2019
$1.6M
Inter-area communications in a decision-making circuitR03MH120426 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2020 to 2020
$158k
NEI NIH HHS P30 EY022589NEI NIH HHS R01 EY025349NIDCD NIH HHS R01 DC018545NIMH NIH HHS R01 MH080047NIMH NIH HHS R01 MH128746NIMH NIH HHS R03 MH120426NINDS NIH HHS R01 NS091010NINDS NIH HHS R35 NS116804
6 · The paper itself

Abstract

The meta-reinforcement learning (meta-RL) framework, which involves RL over multiple timescales, has been successful in training deep RL models that generalize to new environments. It has been hypothesized that the prefrontal cortex may mediate meta-RL in the brain, but the evidence is scarce. Here we show that the orbitofrontal cortex (OFC) mediates meta-RL. We trained mice and deep RL models on a probabilistic reversal learning task across sessions during which they improved their trial-by-trial RL policy through meta-learning. Ca

Indexed as

Reinforcement, PsychologyRewardAnimalsMicePrefrontal CortexReversal Learning

Identifiers

PMID37957318
PMCPMC10689244

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.