Evidence map›Paper›PMID 33760806›Full record

ArticlePLoS computational biology2021

Rational inattention and tonic dopamine.

John G Mikhael, Lucy Lai, Samuel J Gershman

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. 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
3.2field-weighted citation impact, top 8% 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, 35 citations in OpenAlex.

  1. Computationally Informed Insights Into Anhedonia and Treatment by Kappa Opioid Receptor Antagonism.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025
    Trial
  2. Article
  3. Striatal Dopamine Actions and Movement: Inferences from Parkinson Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Review
  4. Article
  5. Policy Complexity Suppresses Dopamine Responses.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  6. Article
  7. Rational inattention in neural coding for economic choice.bioRxiv : the preprint server for biology · 2024
    Article
  8. Policy complexity suppresses dopamine responses.bioRxiv : the preprint server for biology · 2024
    Article
  9. Resource-rational psychopathology.Behavioral neuroscience · 2024
    Review
  10. Article
  11. Article
  12. Bayesian Reinforcement Learning With Limited Cognitive Load.Open mind : discoveries in cognitive science · 2024
    Article
  13. Article
  14. Undermatching Is a Consequence of Policy Compression.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Dopamine firing plays a dual role in coding reward prediction errors and signaling motivation in a working memory task.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  19. Impulsivity and risk-seeking as Bayesian inference under dopaminergic control.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Article
  20. 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 at 1 institution in 1 country.

John G MikhaelProgram in Neuroscience, Harvard Medical School, Boston, Massachusetts, United States of America.ORCID 0000-0002-7622-716X
Lucy LaiProgram in Neuroscience, Harvard Medical School, Boston, Massachusetts, United States of America.
Samuel J GershmanDepartment of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.ORCID 0000-0002-6546-3298
Harvard University · US

Funding

Medical Scientist Training ProgramT32GM007753 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI WALENSKY, LOREN DAVID · 1985 to 2021
$50.0M
Towards a Unified Framework for Dopamine Signaling in the StriatumU19NS113201 · NINDS · HARVARD MEDICAL SCHOOL · PI SABATINI, BERNARDO L · 2019 to 2023
$18.7M
PHD TRAINING IN NEUROSCIENCET32MH020017 · NIMH · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI JOHN ASSAD · 1997 to 2026
$15.8M
NIGMS NIH HHS T32 GM007753NIMH NIH HHS T32 MH020017NINDS NIH HHS U19 NS113201
6 · The paper itself

Abstract

Slow-timescale (tonic) changes in dopamine (DA) contribute to a wide variety of processes in reinforcement learning, interval timing, and other domains. Furthermore, changes in tonic DA exert distinct effects depending on when they occur (e.g., during learning vs. performance) and what task the subject is performing (e.g., operant vs. classical conditioning). Two influential theories of tonic DA-the average reward theory and the Bayesian theory in which DA controls precision-have each been successful at explaining a subset of empirical findings. But how the same DA signal performs two seemingly distinct functions without creating crosstalk is not well understood. Here we reconcile the two theories under the unifying framework of 'rational inattention,' which (1) conceptually links average reward and precision, (2) outlines how DA manipulations affect this relationship, and in so doing, (3) captures new empirical phenomena. In brief, rational inattention asserts that agents can increase their precision in a task (and thus improve their performance) by paying a cognitive cost. Crucially, whether this cost is worth paying depends on average reward availability, reported by DA. The monotonic relationship between average reward and precision means that the DA signal contains the information necessary to retrieve the precision. When this information is needed after the task is performed, as presumed by Bayesian inference, acute manipulations of DA will bias behavior in predictable ways. We show how this framework reconciles a remarkably large collection of experimental findings. In reinforcement learning, the rational inattention framework predicts that learning from positive and negative feedback should be enhanced in high and low DA states, respectively, and that DA should tip the exploration-exploitation balance toward exploitation. In interval timing, this framework predicts that DA should increase the speed of the internal clock and decrease the extent of interference by other temporal stimuli during temporal reproduction (the central tendency effect). Finally, rational inattention makes the new predictions that these effects should be critically dependent on the controllability of rewards, that post-reward delays in intertemporal choice tasks should be underestimated, and that average reward manipulations should affect the speed of the clock-thus capturing empirical findings that are unexplained by either theory alone. Our results suggest that a common computational repertoire may underlie the seemingly heterogeneous roles of DA.

Indexed as

DopamineModels, NeurologicalAttentionBayes TheoremCognitionComputational BiologyHumansReinforcement, PsychologyDopamine

Identifiers

PMID33760806
PMCPMC7990190
OpenAlexW3137135038

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.