Evidence map›Paper›PMID 28406662›Full record

ArticleJournal of abnormal psychology2017

Explicit and implicit reinforcement learning across the psychosis spectrum.

Deanna M Barch, Cameron S Carter, James M Gold, Sheri L Johnson, Ann M Kring, Angus W MacDonald, Diego A Pizzagalli, J Daniel Ragland, Steven M Silverstein, Milton E Strauss

Abstract read
In one paragraph

Article in Journal of abnormal psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

61 citing papers in PubMed.

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  15. Motor precision deficits in clinical high risk for psychosis.European archives of psychiatry and clinical neuroscience · 2024
    Article
  16. Article
  17. Article
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1 more citing papers are in PubMed but not listed here.

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

10 authors.

Deanna M BarchDepartments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis.
Cameron S CarterDepartment of Psychiatry, University of California at Davis.
James M GoldMaryland Psychiatric Research Center.
Sheri L JohnsonDepartment of Psychology, University of California at Berkeley.
Ann M KringDepartment of Psychology, University of California at Berkeley.
Angus W MacDonaldDepartment of Psychology, University of Minnesota.
Diego A PizzagalliDepartment of Psychiatry, Harvard Medical School.
J Daniel RaglandDepartment of Psychiatry, University of California at Davis.
Steven M SilversteinDepartment of Psychiatry, Rutgers University.
Milton E StraussDepartment of Psychology, Case Western Reserve University.

Funding

Cognitive Neurocomputational Task Reliability and Clinical Applications ConsortiumR01MH084840 · NIMH · WASHINGTON UNIVERSITY · PI Deanna Barch, Cameron S. Carter · 2008 to 2026
$8.5M
4/5-Cognitive Neuroscience Task Reliability & Clinical Applications ConsortiumR01MH084821 · NIMH · UNIVERSITY OF MARYLAND BALTIMORE · PI GOLD, JAMES M. · 2008 to 2023
$4.2M
2/5-Cognitive Neuroscience Task Reliability & Clinical Applications ConsortiumR01MH084826 · NIMH · UNIVERSITY OF CALIFORNIA-IRVINE · PI CARTER, CAMERON S. · 2008 to 2023
$4.0M
5/5-Cognitive Neuroscience Task Reliability & Clinical Applications ConsortiumR01MH084861 · NIMH · UNIVERSITY OF MINNESOTA · PI MACDONALD, ANGUS W · 2008 to 2024
$3.8M
Cognitive Neurocomputational Task Reliability & Clinical Applications ConsortiumR01MH084828 · NIMH · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI SILVERSTEIN, STEVEN M · 2008 to 2024
$3.3M
NIMH NIH HHS R01 MH084821NIMH NIH HHS R01 MH084826NIMH NIH HHS R01 MH084828NIMH NIH HHS R01 MH084840NIMH NIH HHS R01 MH084861
6 · The paper itself

Abstract

Motivational and hedonic impairments are core features of a variety of types of psychopathology. An important aspect of motivational function is reinforcement learning (RL), including implicit (i.e., outside of conscious awareness) and explicit (i.e., including explicit representations about potential reward associations) learning, as well as both positive reinforcement (learning about actions that lead to reward) and punishment (learning to avoid actions that lead to loss). Here we present data from paradigms designed to assess both positive and negative components of both implicit and explicit RL, examine performance on each of these tasks among individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis, and examine their relative relationships to specific symptom domains transdiagnostically. None of the diagnostic groups differed significantly from controls on the implicit RL tasks in either bias toward a rewarded response or bias away from a punished response. However, on the explicit RL task, both the individuals with schizophrenia and schizoaffective disorder performed significantly worse than controls, but the individuals with bipolar did not. Worse performance on the explicit RL task, but not the implicit RL task, was related to worse motivation and pleasure symptoms across all diagnostic categories. Performance on explicit RL, but not implicit RL, was related to working memory, which accounted for some of the diagnostic group differences. However, working memory did not account for the relationship of explicit RL to motivation and pleasure symptoms. These findings suggest transdiagnostic relationships across the spectrum of psychotic disorders between motivation and pleasure impairments and explicit RL. (PsycINFO Database Record

Indexed as

LearningModels, PsychologicalReinforcement, PsychologySchizophrenic PsychologyAdultBipolar DisorderCase-Control StudiesFemaleHumansMaleMemory, Short-TermMiddle AgedMotivationPsychotic DisordersReward

Identifiers

PMID28406662
PMCPMC5503766

What OpenQuestion holds

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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.