Evidence map›Paper›PMID 34920884›Full record

ReviewTrends in neurosciences2022

Reinforcement learning detuned in addiction: integrative and translational approaches.

Stephanie M Groman, Summer L Thompson, Daeyeol Lee, Jane R Taylor

Abstract readReview
In one paragraph

Review in Trends in neurosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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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.

Stephanie M GromanDepartment of Neuroscience, University of Minnesota, Minneapolis, MN, USA; Department of Psychiatry, Yale University, New Haven, CT, USA. Electronic address: sgroman@umn.edu.
Summer L ThompsonDepartment of Psychiatry, Yale University, New Haven, CT, USA.
Daeyeol LeeThe Zanvyl Krieger Mind/Brain Institute, The Solomon H. Snyder Department of Neuroscience, Department of Psychological and Brain Sciences, Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA.
Jane R TaylorDepartment of Psychiatry, Yale University, New Haven, CT, USA; Department of Neuroscience, Yale University, New Haven, CT, USA; Department of Psychology, Yale University, New Haven, CT, USA.

Funding

Translational Technologies CoreP50AA012870 · NIAAA · YALE UNIVERSITY · PI John H. Krystal · 2001 to 2026
$43.7M
RESEARCH TRAINING - BIOLOGICAL SCIENCEST32MH014276 · NIMH · YALE UNIVERSITY · PI Marina R Picciotto · 1985 to 2026
$7.2M
Individual differences & cocaine effects on impulsive choice in rats: D3/5HT1B R01DA043443 · NIDA · YALE UNIVERSITY · PI Jane R Taylor · 2016 to 2026
$4.6M
Genomic mechanisms of decision-making and opioid use trajectories in the ratU01DA051977 · NIDA · YALE UNIVERSITY · PI DILEONE, RALPH J, GROMAN, STEPHANIE MARY · 2020 to 2024
$3.2M
Decision-Making Dysfunction and Chronic CocaineR01DA041480 · NIDA · YALE UNIVERSITY · PI TAYLOR, JANE R · 2017 to 2021
$1.7M
Molecular Mechanisms of Susceptibility to Drug Use.K01DA051598 · NIDA · YALE UNIVERSITY · PI GROMAN, STEPHANIE MARY · 2020 to 2024
$800k
The role of the gut microbiota in alcohol seeking and decision-makingK99AA029454 · NIAAA · YALE UNIVERSITY · PI THOMPSON, SUMMER LORETTA · 2021 to 2022
$273k
NIAAA NIH HHS K99 AA029454NIAAA NIH HHS P50 AA012870NIDA NIH HHS K01 DA051598NIDA NIH HHS R01 DA041480NIDA NIH HHS R01 DA043443NIDA NIH HHS U01 DA051977NIMH NIH HHS T32 MH014276
6 · The paper itself

Abstract

Suboptimal decision-making strategies have been proposed to contribute to the pathophysiology of addiction. Decision-making, however, arises from a collection of computational components that can independently influence behavior. Disruptions in these different components can lead to decision-making deficits that appear similar behaviorally, but differ at the computational, and likely the neurobiological, level. Here, we discuss recent studies that have used computational approaches to investigate the decision-making processes underlying addiction. Studies in animal models have found that value updating following positive, but not negative, outcomes is predictive of drug use, whereas value updating following negative, but not positive, outcomes is disrupted following drug self-administration. We contextualize these findings with studies on the circuit and biological mechanisms of decision-making to develop a framework for revealing the biobehavioral mechanisms of addiction.

Indexed as

Behavior, AddictiveSubstance-Related DisordersAnimalsDecision MakingHumansReinforcement, Psychologyamygdaladecision-makingdopaminemGlu5nucleus accumbensorbitofrontal cortex

Identifiers

PMID34920884
PMCPMC8770604

What Socratic 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 Socratic graph.