Evidence map›Paper›PMID 26818509›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2016

Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning.

Bradley B Doll, Kevin G Bath, Nathaniel D Daw, Michael J Frank

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
9.8field-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

48 citing papers in PubMed, 119 citations in OpenAlex.

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  8. Cortical Grey Matter Mediates Increases in Model-Based Control and Learning from Positive Feedback from Adolescence to Adulthood.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
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  17. What is dopamine doing in model-based reinforcement learning?Current opinion in behavioral sciences · 2021
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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

4 authors at 3 institutions in 1 country.

Bradley B DollCenter for Neural Science, New York University, New York, New York 10003, Department of Psychology, Columbia University, New York, New York 10027, bradley.doll@nyu.edu.
Kevin G BathDepartment of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence, Rhode Island 02912.
Nathaniel D DawPrinceton Neuroscience Institute, Princeton University, Princeton, New Jersey 08540, Department of Psychology, Princeton University, Princeton, New Jersey 08540, and.
Michael J FrankDepartment of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence, Rhode Island 02912, Brown Institute for Brain Science, Brown University, Providence, Rhode Island 02912.ORCID http://orcid.org/0000-0001-8451-0523
Brown University · USNew York University · USPrinceton University · US

Funding

Clinical and Computational Studies of Dopamine Function in SchizophreniaR01MH080066 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI GOLD, JAMES M. · 2008 to 2017
$6.4M
Goals vs. habits in the human brain: Cognitive and computational mechanismsR01NS078784 · NINDS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI SHOHAMY, DAPHNA · 2011 to 2014
$1.5M
NIMH NIH HHS R01 MH080066NIMH NIH HHS R01 MH080066-01NINDS NIH HHS R01 NS078784NINDS NIH HHS R01NS078784
6 · The paper itself

Abstract

Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. SIGNIFICANCE STATEMENT: Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes. Research implicates a dopamine-dependent striatal learning mechanism in the former type of choice. Although recent work has indicated that dopamine is also involved in flexible, goal-directed decision-making, it remains unclear whether it also contributes via striatum or via the dopamine-dependent working memory function of prefrontal cortex. We examined genetic indices of dopamine function in these regions and their relation to the two choice strategies. We found that striatal dopamine function related most clearly to the reflexive strategy, as previously shown, and that prefrontal dopamine related most clearly to the flexible strategy. These findings suggest that dissociable brain regions support dissociable choice strategies.

Indexed as

Models, PsychologicalAdolescentAdultBrainBrain MappingCatechol O-MethyltransferaseDecision MakingDopamineDopamine and cAMP-Regulated Phosphoprotein 32FemaleHumansLearningLogistic ModelsMalePolymorphism, Single NucleotideReinforcement, PsychologyCatechol O-MethyltransferaseDopamineDopamine and cAMP-Regulated Phosphoprotein 32PPP1R1B protein, humandecision-makingdopaminegeneticsreinforcement learning

Identifiers

PMID26818509
PMCPMC4728725
OpenAlexW2419503723

What OpenQuestion holds

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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.