SCHIZOPHRENIA 1 (Disorder)CNTRACS 2NCT07875790
Cognitive Neurocomputational Task Reliability and Clinical Applications Consortium: Study 2
A study testing Motion Perception Task, Sine Wave Speech Task and Volatility Task in people with SCHIZOPHRENIA 1 (Disorder) and Schizo Affective Disorder, run by Washington University School of Medicine at 5 sites in United States.
Trial summary
In Study 2, investigators will recruit individuals with schizophrenia (SZ) and or schizoaffective disorder (SZA) and healthy controls (HC) using optimized behavioral tasks to replicate the behavioral findings from Study 1 and to assess additional psychometric properties such as test re-test reliability and practice… Read more about this study
- Who is it for?
- Ages 18 to 59 yearsHealthy volunteers can take part
- Conditions the study is for
- SCHIZOPHRENIA 1 (Disorder), Schizo Affective Disorder, Healthy Adult
- What is being tested?
- Motion Perception Task, Sine Wave Speech Task and Volatility Task
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 325 participants
- Where
- 5 sitesUnited States
- Study dates
- Apr 2028to 30 Jun 2031
- Phase
- Interventional
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 59 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- General Inclusion
- age 18 to 59 ;
- no substance disorder in past six months (confirmed with urine drug screens and breathalyzers);
- no clinically significant head injury or neurological disease;
- WechslerTest of Adult Reading (WTAR) score =16+.
- Group Specific Criteria: Schizophrenia/SchizoaffectiveDisorder (SZ/SZA):
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- Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) diagnosis ofschizophrenia or schizoaffective;
- no medication changes in prior month or anticipated in the next month or not taking medications;
- outpatient or partial hospital if unmedicated
- Healthy Controls (HC):
- no Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) - Psychosis or BipolarDisorder;
- no family history of psychosis or bipolar
Who cannot join
- Healthy Controls (HC):
- Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5)Psychosis or Bipolar Disorder diagnosis
- Family history of psychosis, bipolar, or Schizophrenia/Schizoaffective Disorder (SZ/SZA)
- additional exclusion criteria for the unmedicated individuals are:
- not in acute exacerbation requiring immediate hospitalization or treatment;
- self-reported medication non-compliance for at least the four previous weeks
- never having started medications
Trial locations and contacts
5 sites in 1 country. Contact the study team or a site near you to ask about taking part.
5 sites in 1 country
United States5 sites
University of Maryland, Baltimore
Baltimore, Maryland, 21201
James Gold, MD, (410) 402-7871, jgold@som.umaryland.edu
The University of Chicago
Chicago, Illinois, 60637
Molly Erickson, PhD, (773) 702-5855, merickson1@yoda.bsd.uchicago.edu
Nicole Ogbuagu, 773-795-2633, nicoleogbuagu@uchicago.edu
University of California Irvine
Irvine, California, 92868
Cameron Carter, MD, 916-734-2972, cscarte1@hs.uci.edu
University of Minnesota
Minneapolis, Minnesota, 55455
Angus Macdonald III, PhD, 612-624-3813, angus@umn.edu
Alyssa Zimmerman, 651-558-1275, zimme857@umn.edu
Washington University
St Louis, Missouri, 63110
Deanna Barch, Ph.D., 314-935-8729, dbarch@wustl.edu
Lori Ingram, 314-747-2160, ingram@wustl.edu
About this study
Official title: Cognitive Neurocomputational Task Reliability and Clinical Applications Consortium
In Study 2, investigators will recruit individuals with schizophrenia (SZ) and or schizoaffective disorder (SZA) and healthy controls (HC) using optimized behavioral tasks to replicate the behavioral findings from Study 1 and to assess additional psychometric properties such as test re-test reliability and practice effects.
Investigators will obtain data on: A) clinical symptoms, with detailed assessment of hallucinations and delusions; B) community functioning; and C) functional capacity, allowing us to examine clinical validity. To generate a sample with sufficient variation in hallucinations and delusions, investigators will recruit the following groups that balance feasibility with clinical relevance: A) healthy controls [HC, N=125]; B) schizophrenia and schizoaffective disorder [SZ/SZA, N=200]). Investigators anticipate a ~20% screen fail/drop-out rate based upon prior studies. Thus, investigators will run an additional 40 SZ/SZA and 15 HC.
Read more
Investigators will administer tasks optimized in Aim 1 without electroencephalogram (EEG), to this new sample of individuals with SZ/SZA and HC.
All participants will be retested after approximately 28 days and repeat clinical assessments. Although the investigators' goal is to shorten task length using the Study 1 analyses, they will administer longer tasks than optimal for public dissemination in Study 2 to determine the minimum number of trials required for acceptable reliability. Study 2 will use the same clinical and functional measures as Study 1.
Read the detailed description
Each participant will complete 3 sessions (~3 hours each) within 3 weeks at baseline. The first session includes clinical, self-report, proxy function, and community function assessments. Sessions 2-3 are for task. Each participant will complete 7 tasks across these sessions. Task order will be counterbalanced across sessions. Participants will return after 28 days and repeat these same 3 sessions.
Clinical Assessment and Self-Report: A trained assessor will diagnose participants using the Structured Clinical Interview (SCID-5) for Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) Text Revision 59 (TR59). Clinicians will rate hallucination and delusion symptom severity with the Chicago Hallucinations Assessment Tool (CHAT) and the Brief Psychiatric Rating Scale (BPRS). Investigators will use the Psychotic Symptom Rating Scales (PSYRATS) to evaluate the degree of preoccupation, conviction, distress, and life disruption associated with hallucinations and delusions elicited on the BPRS and CHAT. To address specificity, investigators will administer the Clinical Assessment Interview for Negative Symptoms (CAINS). For self-report, investigators will use the Beliefs about Voices Scale which assesses attributions about the origin and power of voices, and the Yale Control Over Perceptual Experiences (COPE) scale, which evaluates the extent to which people feel they can exert control over their voices. Investigators also will use the Peters Delusion Inventory to assess the extent of delusional thinking, supplemented by the Green Paranoia Scale to provide additional coverage of persecutory beliefs. To assess specificity, investigators will use the Patient Health Questionnaire (PHQ-9) to assess depression, the Generalized Anxiety Disorder Scale (GAD-7) to assess anxiety, and the Motivation and Pleasure Scale-Self-Report (MAP-SR) to assess anhedonia and motivation. Investigators will conduct a principal components analysis (PCA) on measures of the same construct (e.g., delusions) and perform primary analyses using the first principal component, followed by secondary analyses of specific measures False Discovery Rate (FDR) correction.
Community Function: Patients will complete the Specific Levels of Functioning (SLOF) scale, a validated scale of work and community function. National Institute of Mental Health (NIMH) Common Data Elements: Investigators will acquire the additional NIMH Tier 1 Common Data elements (e.g., World Health Organization Disability Assessment Schedule 2 (WHODAS 2.0) \& DSM-5 Symptom Measure). Investigators will include standard general cognitive measures to assess the specificity of effects beyond general cognitive impairment. Specifically, investigators will include validated online measures from TestMyBrain (https://www.testmybrain.org/using-tmb/research.html; Digit Symbol Coding, Vocabulary, and Matrix Reasoning), as in our prior work in both clinical and healthy populations.
- Being tested
- Motion Perception Task, Sine Wave Speech Task, Volatility Task, Choice Probabilistic Reversal Task, Kamin Blocking Task
- Keywords
- schizophrenia, schizo-affective, healthy controls
- Medical subject headings
- Psychotic Disorders, Schizophrenia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Motion Perception TaskBehavioural
Assesses updating of beliefs from new sensory inputs with prior knowledge via perceiving direction changes in random dot motion stimuli
Sine Wave Speech TaskBehavioural
Measures the degree to which overweighting of prior beliefs impacts processing of sensory inputs (detection of speech).
Volatility TaskBehavioural
Measures the updating of priors about the location of a bag drop from a helicopter when the location changes (prediction errors).
Choice Probabilistic Reversal TaskBehavioural
Assesses prior belief updating when feedback about obtaining positive outcomes changes (prediction errors).
Kamin Blocking TaskBehavioural
Examines the role of mismatches between learned priors and new information (prediction errors) in belief formation about event causes.
Minnesota Trust GameBehavioural
Assesses the degree to which people distinguish between their priors about others' motivations, such as selfishness and spite, and impersonal chance in one-shot trust game and dictator games.
Dynamic Trust GameBehavioural
Assesses degree to which people learn and update priors about trusting partners from dynamic social feedback (prediction error) in a social exchange game.
What is being measured
The primary outcome is the main question the study is designed to answer.
Motion Perception Task Performance
With 15 degrees of initial or changed direction vs. the probability of failing to update
Measured: 1 hour
Sine Wave Speech Task Performance
Percentage of trials coded as speech or not vs Dprime
Measured: 1 hour
Volatility Task Performance
Percent correct bag captures during periods of stability vs. instability - patients worse in both, but particularly impaired in instability vs. Environmental volatility belief parameter
Measured: 1 hour
Choice Probabilistic Reversal Performance Task
Win-switch rate (higher in patients, particularly paranoid patients) vs. (prior on volatility belief updating in response to volatility
Measured: 1 hour
Kamin Blocking Task Performance
Number of times participant predict allergy following blocked cue vs. prediction errors and learning rates
Measured: 1 hour
Minnesota Trust Game Performance
Percent of trusting choices depending on decision-agent and temptation vs. spite-guilt beliefs estimate
Measured: 1 hour
Dynamic Trust Game Performance
Trust indexed by mean investment versus learning rates
Measured: 1 hour
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Oct 2026
- Study startApr 2028 (estimated)
- Primary completion30 Jun 2031 (estimated)
- Study completion30 Jun 2031 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (30)Papers the sponsor has linked to this study.
- Other trials for SCHIZOPHRENIA 1 (Disorder)Studies of the same condition, open and under way.
- More trials run by Washington University School of MedicineThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 325 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Washington University School of Medicine
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of Mental Health (NIMH), University of Minnesota, University of Chicago, University of California, Irvine, University of Maryland, Baltimore County
- Responsible party
- Principal investigator, Deanna Barch, Washington University School of Medicine
- Investigators
- Deanna Barch, PhD, Principal investigator, Washington University School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07875790
- Sponsor's protocol ID
- 201904012: Study 2
- Other IDs
- 2R01MH084840
- Acronym
- CNTRACS 2
- Status last verified
- Oct 2026
- First submitted
- 8 Oct 2026
- Last updated
- 23 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Our plan is to share de-identified participant data through the National Data Archive (NDA) as required by the National Institute of Mental Health (NIMH)
Publications
Boudewyn MA, Erickson MA, Winsler K, Ragland JD, Yonelinas A, Frank M, Silverstein SM, Gold J, MacDonald AW 3rd, Carter CS, Barch DM, Luck SJ. Managing EEG studies: How to prepare and what to do once data collection has begun. Psychophysiology. 2023 Nov;60(11):e14365. doi: 10.1111/psyp.14365. Epub 2023 Jun 14.
PubMed 37314113Li C, Boudewyn MA, Barch DM, Carter CS, Frank MJ, Gold JM, MacDonald AW 3rd, Ragland JD, Silverstein SM, Yonelinas A, Luck SJ, Erickson MA. Impacted and preserved sub-domains of cognitive control in schizophrenia. Neuropsychologia. 2026 Sep 9;230:109503. doi: 10.1016/j.neuropsychologia.2026.109503. Epub 2026 May 25.
PubMed 42184934Boudewyn MA, Erickson MA, Winsler K, Barch DM, Carter CS, Frank MJ, Gold JM, MacDonald AW 3rd, Ragland JD, Silverstein SM, Yonelinas AP, Luck SJ. Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders. Schizophr Bull. 2025 Mar 14;51(2):543-555. doi: 10.1093/schbul/sbae038.
PubMed 38616053MacDonald AW, Patzelt E, Kurth-Nelson Z, Barch DM, Carter CS, Gold JM, Ragland JD, Silverstein SM. Computational modeling of reversal learning impairments in schizophrenia and bipolar disorder reveals shared failure to exploit rewards. J Psychopathol Clin Sci. 2025 Apr;134(3):262-271. doi: 10.1037/abn0000944. Epub 2025 Mar 10.
PubMed 40063391Erickson MA, Boudewyn MA, Winsler K, Li C, Barch DM, Carter CS, Frank MJ, Gold JM, MacDonald AW 3rd, Ragland JD, Silverstein SM, Yonelinas A, Luck SJ. Dysfunctional Alpha Modulation as a Mechanism of Working Memory Impairment in Serious Mental Illness. Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Dec;9(12):1271-1280. doi: 10.1016/j.bpsc.2024.07.022. Epub 2024 Aug 6.
PubMed 39117276Barch DM, Boudewyn MA, Carter CC, Erickson M, Frank MJ, Gold JM, Luck SJ, MacDonald AW 3rd, Ragland JD, Ranganath C, Silverstein SM, Yonelinas A. Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions. Curr Top Behav Neurosci. 2023;63:19-60. doi: 10.1007/7854_2022_391.
PubMed 36173600Rac-Lubashevsky R, Cremer A, Collins AGE, Frank MJ, Schwabe L. Neural Index of Reinforcement Learning Predicts Improved Stimulus-Response Retention under High Working Memory Load. J Neurosci. 2023 Apr 26;43(17):3131-3143. doi: 10.1523/JNEUROSCI.1274-22.2023. Epub 2023 Mar 17.
PubMed 36931706Kwashie AN, Ma Y, Barch DM, Chafee M, Ragland JD, Silverstein SM, Carter CS, Gold JM, MacDonald AW 3rd. Comparing the functional neuroanatomy of proactive and reactive control between patients with schizophrenia and healthy controls. Cogn Affect Behav Neurosci. 2023 Feb;23(1):203-215. doi: 10.3758/s13415-022-01036-6. Epub 2022 Nov 23.
PubMed 36418846Liu RG, Frank MJ. Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning. Artif Intell. 2022 Nov;312:103770. doi: 10.1016/j.artint.2022.103770. Epub 2022 Aug 5.
PubMed 36711165Pratt DN, Barch DM, Carter CS, Gold JM, Ragland JD, Silverstein SM, MacDonald AW. Reliability and Replicability of Implicit and Explicit Reinforcement Learning Paradigms in People With Psychotic Disorders. Schizophr Bull. 2021 Apr 29;47(3):731-739. doi: 10.1093/schbul/sbaa165.
PubMed 33914891Geana A, Barch DM, Gold JM, Carter CS, MacDonald AW 3rd, Ragland JD, Silverstein SM, Frank MJ. Using Computational Modeling to Capture Schizophrenia-Specific Reinforcement Learning Differences and Their Implications on Patient Classification. Biol Psychiatry Cogn Neurosci Neuroimaging. 2022 Oct;7(10):1035-1046. doi: 10.1016/j.bpsc.2021.03.017. Epub 2021 Apr 18.
PubMed 33878489Hamid AA, Frank MJ, Moore CI. Wave-like dopamine dynamics as a mechanism for spatiotemporal credit assignment. Cell. 2021 May 13;184(10):2733-2749.e16. doi: 10.1016/j.cell.2021.03.046. Epub 2021 Apr 15.
PubMed 33861952Moran EK, Gold JM, Carter CS, MacDonald AW 3rd, Ragland JD, Silverstein SM, Luck SJ, Barch DM. Both unmedicated and medicated individuals with schizophrenia show impairments across a wide array of cognitive and reinforcement learning tasks. Psychol Med. 2022 Apr;52(6):1115-1125. doi: 10.1017/S003329172000286X. Epub 2020 Aug 17.
PubMed 32799938Pedersen ML, Frank MJ. Simultaneous Hierarchical Bayesian Parameter Estimation for Reinforcement Learning and Drift Diffusion Models: a Tutorial and Links to Neural Data. Comput Brain Behav. 2020 Dec;3(4):458-471. doi: 10.1007/s42113-020-00084-w. Epub 2020 May 26.
PubMed 35128308Ray KL, Ragland JD, MacDonald AW, Gold JM, Silverstein SM, Barch DM, Carter CS. Dynamic reorganization of the frontal parietal network during cognitive control and episodic memory. Cogn Affect Behav Neurosci. 2020 Feb;20(1):76-90. doi: 10.3758/s13415-019-00753-9.
PubMed 31811557