Improving deep brain stimulation with MRI and AI
Official title: Functional Magnetic Resonance Imaging and Deep Learning to Improve Deep Brain Stimulation Therapy
Funded at Ge Medical Systems Information Technologies, INC · NIH-11478774 · Data updated 2026-11-12
We use brain scans and artificial intelligence to speed up and personalize deep brain stimulation settings for people getting DBS.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Ge Medical Systems Information Technologies, INC NIH-funded |
| Lab location | 1 site (Niskayuna, United States) |
| Project start | September 19, 2023 |
| Project end | November 30, 2028 |
| Funding year | 2026 |
| Award (this year) | $262,823 |
| NIH project number | 3R01NS133433-04S1 |
| Project ID | NIH-11478774 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people with Parkinson's disease or other movement disorders who are considering or already receiving deep brain stimulation.
✕Less likely to help
People who do not have DBS, are not eligible for DBS, or have implants or health conditions incompatible with MRI or DBS programming may not benefit.
What this research studies
The team will use functional MRI scans combined with deep-learning algorithms to predict optimal stimulation contacts and pulse settings. They plan to train models using imaging and clinical response data from patients with movement disorders who have different DBS electrode types. The goal is to reduce the long trial-and-error process that currently takes many clinic visits and months to reach good settings. Participants would provide scans and symptom data while AI-guided programming is compared with usual clinical tuning.
Why it matters
Potential benefit: If successful, this could shorten the time to find the best DBS settings, lower side effects, and improve symptom control.
How similar studies have gone: Some prior work has shown promise using AI and imaging to help DBS programming, but combining functional MRI with deep-learning automated programming remains an emerging approach.
Where this research is happening
-
Ge Medical Systems Information Technologies, INC
Niskayuna, United States Active
Researchers
- Principal investigator: Ajala, Afis — Ge Medical Systems Information Technologies, INC
- Study coordinator: Ajala, Afis
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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.