Global Deep Learning effort to predict depression treatment response
Official title: Global Deep Learning Initiative to Understand Outcomes in Major Depression
Funded at University of Southern California · NIH-11519980 · Data updated 2026-11-12
A patient-focused project uses AI on brain scans to predict who with major depression will respond to rTMS treatment.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Southern California NIH-funded |
| Lab location | 1 site (Los Angeles, UNITED STATES) |
| Project start | June 1, 2023 |
| Project end | March 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $140,400 |
| NIH project number | 3R01MH131806-04S1 |
| Project ID | NIH-11519980 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with major depressive disorder who may be candidates for rTMS therapy.
✕Less likely to help
Patients not considering rTMS or without depression may not benefit from this specific approach.
What this research studies
This project brings together international experts to analyze brain images from people with major depressive disorder using advanced AI. By applying multimodal MRI data and novel neural networks, the researchers hope to identify brain features that predict who will benefit from rTMS therapy. The goal is to personalize treatment so patients receive the most promising option sooner. Privacy-protecting techniques will be used while learning from large datasets across different groups. If successful, this work could lead to better targeting of rTMS and faster relief for many patients.
Why it matters
Potential benefit: Better, faster matching of patients to effective rTMS treatment could improve outcomes and reduce time to relief.
How similar studies have gone: Prior studies show promise for AI-driven prediction in brain disorders, but this project aims to generalize across datasets and improve prediction for depression treatment.
Where this research is happening
-
University of Southern California
Los Angeles, United States Active
Researchers
- Principal investigator: Thompson, Paul M — University of Southern California
- Study coordinator: Thompson, Paul M
Related research
Other NIH-funded projects on the same topics.
-
Global Deep Learning to Predict Depression Treatment Response
Researchers are using advanced AI on brain scans to predict which people with major depressive disorder will respond to rTMS treatment.
-
Trans-Nordic look at extreme major depression genetics
A large genetics study is exploring what makes extreme forms of major depression unique, by studying many thousands of people and their DNA.
-
Genetic factors behind alcohol and opioid use disorders and depression in veterans
A study using genetic data from veterans to understand how genes contribute to co-occurring alcohol use, prescription opioid use, and depression.
-
Understanding immune dysfunction and social stress in veterans with depression
A study in U.S. veterans with major depressive disorder looks at how stress-related immune changes may be linked to depression and heart health.
-
Risk pathways to major depression using big Danish and Swedish data
A large study using health and genetic data from Denmark and Sweden will help understand what genetic and environmental factors contribute to major depression across how people grow up.
-
Understanding genetic and environmental pathways to major depression in Nordic health records
A large study will look at how genes and life experiences combine over time to influence major depression, using Danish and Swedish population data.
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.