Identifying brain markers to improve depression treatment selection
Official title: Establishing Multimodal Brain Biomarkers Using Data-driven Analyticsfor Treatment Selection in Depression
Funded at Lehigh University · NIH-11042272 · Data updated 2026-11-12
This study is looking to create smart tools that use brain scans to help figure out which depression treatments might work best for you, so you can get the right help faster and with less guesswork.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Lehigh University NIH-funded |
| Lab location | 1 site (Bethlehem, United States) |
| Project start | May 1, 2023 |
| Project end | February 29, 2028 |
| Funding year | 2025 |
| Award (this year) | $566,267 |
| NIH project number | 5R01MH129694-03 |
| Project ID | NIH-11042272 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with major depression who are seeking treatment options.
✕Less likely to help
Patients with depression who are not interested in medication or those with treatment-resistant depression may not benefit from this research.
What this research studies
This research aims to develop advanced analytical tools that utilize machine learning and large-scale neuroimaging data to identify brain biomarkers associated with treatment responses in patients with depression. By analyzing data from functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), the project seeks to uncover neurobiological patterns that can predict how well patients will respond to antidepressant medications. This approach aims to reduce the trial-and-error process often involved in finding effective treatments, ultimately leading to faster and more personalized care for individuals suffering from depression.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatment options for patients with depression, improving their chances of recovery.
How similar studies have gone: Previous research has shown promise in using neuroimaging and machine learning to identify biomarkers for various mental health conditions, suggesting that this approach could yield valuable insights for depression treatment as well.
Where this research is happening
-
Lehigh University
Bethlehem, United States Active
Researchers
- Principal investigator: Zhang, Yu — Lehigh University
- Study coordinator: Zhang, Yu
Related research
Other NIH-funded projects on the same topics.
-
Biotype-based Personalization of Antidepressant Augmentation in Late-Life Depression
A multi-site study will test a computer-guided approach to choosing the best augmentation option for older adults with treatment-resistant depression.
-
Suubi-Mhealth: a mobile app to help Ugandan youth with HIV manage depression and ART adherence
A mobile app designed for 14–17 year olds in Uganda aims to support mental health and keep HIV treatment on track.
-
Group-based postpartum depression prevention: in-person vs. virtual delivery
A large study is testing whether the ROSE group program delivered virtually to pregnant people is just as helpful as the in-person version in preventing postpartum depression.
-
DESCANSO: A friendly CBT plan to ease depression, sleep problems, and fatigue in Latino cancer patients
A Spanish-speaking CBT program called DESCANSO is being tested to help Latino cancer patients feel less tired, sleep better, and happier.
-
Personalized iTBS for Depression: Faster, Targeted Brain Stimulation
A personalized, time-efficient brain stimulation approach may help people with treatment-resistant depression achieve better relief using tailored iTBS settings.
-
Ultrasound-guided brain circuit targets for treatment-resistant depression
This grant tests whether focused ultrasound can safely and reversibly adjust brain circuits linked to negative mood in people with treatment-resistant depression.
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.