Analyzing brain activity patterns using advanced imaging techniques
Official title: Deep Generative Analyses for fMRI data
Funded at Duke University · NIH-10954265 · Data updated 2026-11-12
This study is looking for ways to better understand how brain activity relates to mental health issues by using advanced computer techniques, and it invites patients to help by sharing their fMRI scans, which could lead to more personalized treatments.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project start | November 1, 2023 |
| Project end | October 31, 2025 |
| Funding year | 2025 |
| Award (this year) | $42,125 |
| NIH project number | 5F30MH129086-02 |
| Project ID | NIH-10954265 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation include adults over 21 years old who are experiencing mental health issues.
✕Less likely to help
Patients with no mental health conditions or those under 21 years old may not benefit from this research.
What this research studies
This research focuses on developing new methods to analyze functional MRI (fMRI) data to better understand mental illnesses. By using advanced machine learning techniques, specifically deep generative models, the research aims to capture the complex dynamics of brain activity and individual differences in patients. The goal is to improve the understanding of how brain abnormalities relate to mental health conditions, which could lead to more personalized treatment approaches. Patients may be involved in providing fMRI data that can help refine these analytical methods.
Why it matters
Potential benefit: If successful, this research could lead to improved diagnostic tools and treatment strategies for mental illnesses.
How similar studies have gone: Previous research has shown promise in using machine learning techniques for analyzing brain imaging data, indicating potential for success in this approach.
Where this research is happening
-
Duke University
Durham, United States Active
Researchers
- Principal investigator: De Albuquerque, Daniela Frank — Duke University
- Study coordinator: De Albuquerque, Daniela Frank
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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.