Evidence map›Paper›PMID 36173600›Full record

ArticleCurrent topics in behavioral neurosciences2023

Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions.

Deanna M Barch, Megan Ann Boudewyn, Cameron C Carter, Molly Erickson, Michael J Frank, James M Gold, Steven J Luck, Angus W MacDonald, J Daniel Ragland, Charan Ranganath and 2 more

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In one paragraph

Article in Current topics in behavioral neurosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. DifferentialScience advances · 2026
    Article
  2. Review
  3. Review
  4. 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 at 7 institutions in 1 country.

Deanna M BarchDepartment of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA. dbarch@wustl.edu.
Megan Ann BoudewynUniversity of California, Santa Cruz, CA, USA.
Cameron C CarterUniversity of California, Davis, CA, USA.
Molly EricksonUniversity of Chicago, Chicago, IL, USA.
Michael J FrankBrown University, Providence, RI, USA.
James M GoldMaryland Psychiatric Research Center, Baltimore, MD, USA.
Steven J LuckUniversity of California, Davis, CA, USA.
Angus W MacDonaldUniversity of Minnesota, Minneapolis, MN, USA.
J Daniel RaglandUniversity of California, Davis, CA, USA.
Charan RanganathUniversity of California, Davis, CA, USA.
Steven M SilversteinUniversity of Rochester, Rochester, NY, USA.
Andy YonelinasUniversity of California, Davis, CA, USA.
University of California, Davis · USBrown University · USUniversity of California, Santa Cruz · USUniversity of Illinois Chicago · USUniversity of Minnesota · USUniversity of Rochester · USWashington University in St. Louis · US

Funding

Cognitive Neurocomputational Task Reliability and Clinical Applications ConsortiumR01MH084840 · NIMH · WASHINGTON UNIVERSITY · PI Deanna Barch, Cameron S. Carter · 2008 to 2026
$8.5M
NIMH NIH HHS R01 MH084840
6 · The paper itself

Abstract

The development of treatments for impaired cognition in schizophrenia has been characterized as the most important challenge facing psychiatry at the beginning of the twenty-first century. The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) project was designed to build on the potential benefits of using tasks and tools from cognitive neuroscience to better understanding and treat cognitive impairments in psychosis. These benefits include: (1) the use of fine-grained tasks that measure discrete cognitive processes; (2) the ability to design tasks that distinguish between specific cognitive domain deficits and poor performance due to generalized deficits resulting from sedation, low motivation, poor test taking skills, etc.; and (3) the ability to link cognitive deficits to specific neural systems, using animal models, neuropsychology, and functional imaging. CNTRICS convened a series of meetings to identify paradigms from cognitive neuroscience that maximize these benefits and identified the steps need for translation into use in clinical populations. The Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRaCS) Consortium was developed to help carry out these steps. CNTRaCS consists of investigators at five different sites across the country with diverse expertise relevant to a wide range of the cognitive systems identified as critical as part of CNTRICs. This work reports on the progress and current directions in the evaluation and optimization carried out by CNTRaCS of the tasks identified as part of the original CNTRICs process, as well as subsequent extensions into the Positive Valence systems domain of Research Domain Criteria (RDoC). We also describe the current focus of CNTRaCS, which involves taking a computational psychiatry approach to measuring cognitive and motivational function across the spectrum of psychosis. Specifically, the current iteration of CNTRaCS is using computational modeling to isolate parameters reflecting potentially more specific cognitive and visual processes that may provide greater interpretability in understanding shared and distinct impairments across psychiatric disorders.

Indexed as

Psychotic DisordersSchizophreniaAnimalsCognitionDisease Models, AnimalReproducibility of ResultsCNTRaCSCNTRICSCognitive neurosciencePositive valence systemsSchizophrenia

Identifiers

PMID36173600
OpenAlexW4297964752

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.