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Can Computational Measures of Task Performance Predict Psychiatric Symptoms and Changes in Symptom Severity Across Time
Sponsor: California Institute of Technology
Summary
This study investigates the computational mechanisms associated with psychiatric disease dimensions. The study will characterize the relationship between computational parameter estimates of task performance and psychiatric symptoms and diagnoses with a longitudinal approach over a 12 month interval. Participants will be healthy participants recruited through Prolific an on-line crowdsourcing service, and psychiatric patients and healthy participants recruited via UCLA Psychiatry Clinics and UCLA's STAND Program
Official title: Leveraging Computationally Derived Measures of Individual Differences in Learning and Decision-making to Predict Psychiatric Diagnosis, Symptoms and Changes in Symptom Severity Across Time
Key Details
Gender
All
Age Range
18 Years - 65 Years
Study Type
INTERVENTIONAL
Enrollment
1100
Start Date
2025-01-01
Completion Date
2029-12-31
Last Updated
2024-11-26
Healthy Volunteers
Yes
Interventions
Behavioral task performance
Measures of performance on behavioral tasks
Locations (2)
UCLA Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
Los Angeles, California, United States
California Insitute of Technology
Pasadena, California, United States