Evidence map›Paper›PMID 42765980›Full record

ArticleJournal of psychopathology and clinical science2026

Reliability of computational versus noncomputational metrics of working memory and episodic memory in serious mental illness.

Kurt Winsler, Deanna M Barch, Megan A Boudewyn, Cameron S Carter, Molly A Erickson, Michael J Frank, James M Gold, Angus W MacDonald, J Daniel Ragland, Steven M Silverstein and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of psychopathology and clinical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Kurt WinslerCenter for Mind and Brain, University of California, Davis.
Deanna M BarchDepartment of Psychological and Brain Sciences, Washington University in St. Louis.
Megan A BoudewynDepartment of Psychology, University of California, Santa Cruz.
Cameron S CarterDepartment of Psychiatry and Human Behavior, University of California, Irvine, School of Medicine.
Molly A EricksonDepartment of Psychiatry and Behavioral Neuroscience, University of Chicago.
Michael J FrankDepartment of Cognitive, Linguistic, and Psychological Sciences, Brown University.
James M GoldMaryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine.
Angus W MacDonaldDepartment of Psychology, University of Minnesota.
J Daniel RaglandDepartment of Psychiatry and Behavioral Neuroscience, University of Chicago.
Steven M SilversteinDepartment of Psychiatry, University of Rochester Medical Center.
Andrew P YonelinasCenter for Mind and Brain, University of California, Davis.
Steven J LuckCenter for Mind and Brain, University of California, Davis.ORCID 0000-0002-3725-1474

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 HHSNIMH 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

Computational models can be used to decompose overall behavior into individual parameters that are designed to isolate specific cognitive and neural processes and provide new information about psychiatric disorders. However, it is not yet clear whether these computational parameters have sufficient reliability to replace traditional noncomputational metrics, especially in severe mental illness. The present study asked whether computational parameters can be as reliable as, or even more reliable than, noncomputational performance metrics in healthy control participants (

Indexed as

Bipolar DisorderComputer SimulationMajor Depressive DisorderMemory, EpisodicMemory, Short-TermSchizophreniaAdultFemaleHumansMaleMiddle AgedNeuropsychological TestsReproducibility of ResultsYoung Adult

Identifiers

PMID42765980
PMCPMC13595892

What OpenQuestion holds

Textmetadata
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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.