Evidence map›Paper›PMID 32500968›Full record

ArticleHuman brain mapping2020

Dark control: The default mode network as a reinforcement learning agent.

Elvis Dohmatob, Guillaume Dumas, Danilo Bzdok

Abstract read
In one paragraph

Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 3 pooled it
–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

59 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Narrative "twist" shifts within-individual neural representations of dissociable story features.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  9. Sex-Specific Associations of Irritability With Subcortical Brain Volumes.Biological psychiatry global open science · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. An Active-Inference Approach to Second-Person Neuroscience.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024
    Review
  20. Temporal complexity of the BOLD-signal in preterm versus term infants.Cerebral cortex (New York, N.Y. : 1991) · 2024
    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

3 authors.

Elvis DohmatobCriteo AI Lab, Paris, France.
Guillaume DumasInstitut Pasteur, Human Genetics and Cognitive Functions Unit, Paris, France.ORCID 0000-0002-2253-1844
Danilo BzdokDepartment of Biomedical Engineering, McConnell Brain Imaging Centre, Montreal Neurological Institute, Faculty of Medicine, School of Computer Science, McGill University, Montreal, Canada.

Funding

Amazon AWS Research GrantCanada First Research Excellence fundCanada Institute for Advanced ResearchDeutsche Forschungsgemeinschaft BZ2/2-1Deutsche Forschungsgemeinschaft BZ2/3-1Deutsche Forschungsgemeinschaft BZ2/4-1Exploratory Research Space OPSF449German National Merit FoundationInnovative Medicines Initiative 777394International Research Training Group IRTG2150Seventh Framework Programme 604102START-Program of the Faculty of Medicine 126/16Studienstiftung des Deutschen Volkes
6 · The paper itself

Abstract

The default mode network (DMN) is believed to subserve the baseline mental activity in humans. Its higher energy consumption compared to other brain networks and its intimate coupling with conscious awareness are both pointing to an unknown overarching function. Many research streams speak in favor of an evolutionarily adaptive role in envisioning experience to anticipate the future. In the present work, we propose a process model that tries to explain how the DMN may implement continuous evaluation and prediction of the environment to guide behavior. The main purpose of DMN activity, we argue, may be described by Markov decision processes that optimize action policies via value estimates through vicarious trial and error. Our formal perspective on DMN function naturally accommodates as special cases previous interpretations based on (a) predictive coding, (b) semantic associations, and (c) a sentinel role. Moreover, this process model for the neural optimization of complex behavior in the DMN offers parsimonious explanations for recent experimental findings in animals and humans.

Indexed as

Models, TheoreticalReinforcement, PsychologyAnticipation, PsychologicalCerebral CortexDefault Mode NetworkExecutive FunctionHippocampusHumansMarkov ChainsThinkingartificial intelligencehuman intelligencesystems neuroscience

Identifiers

PMID32500968
PMCPMC7375062

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.