Predicting psychiatric symptoms from brain-based learning patterns
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
Funded at California Institute of Technology · NIH-11322587 · Data updated 2026-11-12
This grant will study how differences in learning and decision-making patterns, measured with computer tasks, relate to anxiety and other psychiatric symptoms over time.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | California Institute of Technology NIH-funded |
| Lab location | 1 site (Pasadena, United States) |
| Project start | April 17, 2025 |
| Project end | January 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $750,825 |
| NIH project number | 5R01MH138895-02 |
| Project ID | NIH-11322587 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals with anxiety-related conditions who can complete computerized task batteries and participate in longitudinal assessments.
✕Less likely to help
People who cannot complete computer-based tasks or who are not followed over time may not benefit from this research.
What this research studies
Researchers will use a battery of computational tasks to capture how people learn and make choices, and then relate these patterns to anxiety and related conditions. The study aims to identify reliable brain-behavior measures that can track changes in symptoms over months and years. By separating day-to-day fluctuations, short-term changes, and stable traits, the project seeks to understand which patterns best predict diagnosis and treatment outcomes. This information could ultimately help tailor more personalized approaches for people with anxiety and related conditions.
Why it matters
Potential benefit: If successful, the work could improve how clinicians predict and monitor psychiatric symptoms and tailor treatments.
How similar studies have gone: Similar computational approaches have shown promise in linking learning patterns to psychiatric symptoms, though this project advances methodology and longitudinal tracking.
Where this research is happening
-
California Institute of Technology
Pasadena, United States Active
Researchers
- Principal investigator: O'doherty, John P — California Institute of Technology
- Study coordinator: O'doherty, John P
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.