Evidence map›Paper›PMID 37082448›Full record

ArticleCurrent opinion in behavioral sciences2021

What is dopamine doing in model-based reinforcement learning?

Thomas Akam, Mark E Walton

Open access · greenAbstract read
In one paragraph

Article in Current opinion in behavioral sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

13 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Building Goal-Directed Cognitive Graphs.bioRxiv : the preprint server for biology · 2026
    Article
  3. A brief history of dopamine prediction errors.Frontiers in computational neuroscience · 2026
    Review
  4. Data-driven equation discovery reveals nonlinear reinforcement learning in humans.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Dopamine Release in the Nucleus Accumbens Core Encodes the General Excitatory Components of Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  10. Article
  11. Article
  12. Review
  13. 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

2 authors at 1 institution in 1 country.

Thomas AkamDepartment of Experimental Psychology, Oxford University, Oxford, UK.
Mark E WaltonDepartment of Experimental Psychology, Oxford University, Oxford, UK.
University of Oxford · GB

Funding

Wellcome Trust 202831Wellcome Trust 202831/Z/16/Z
6 · The paper itself

Abstract

Experiments have implicated dopamine in model-based reinforcement learning (RL). These findings are unexpected as dopamine is thought to encode a reward prediction error (RPE), which is the key teaching signal in model-free RL. Here we examine two possible accounts for dopamine's involvement in model-based RL: the first that dopamine neurons carry a prediction error used to update a type of predictive state representation called a successor representation, the second that two well established aspects of dopaminergic activity, RPEs and surprise signals, can together explain dopamine's involvement in model-based RL.

Identifiers

PMID37082448
PMCPMC7614453
OpenAlexW3107123484

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.