MRI and AI to personalize deep brain stimulation for Parkinson's
Official title: Functional Magnetic Resonance Imaging and Deep Learning to Improve Deep Brain Stimulation Therapy
Funded at Ge Medical Systems Information Technologies, INC · NIH-11263609 · Data updated 2026-11-12
This project uses brain MRI and artificial intelligence to help personalize deep brain stimulation settings so people with Parkinson's get faster, safer symptom relief.
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) | $326,433 |
| NIH project number | 5R01NS133433-04 |
| Project ID | NIH-11263609 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with Parkinson's disease or other movement disorders who are candidates for, or already have, deep brain stimulation implants and can undergo MRI and follow-up programming visits.
✕Less likely to help
Patients who are not DBS candidates, cannot safely have MRI (for example, because of incompatible hardware), or have severe cognitive or medical issues preventing participation are unlikely to benefit directly.
What this research studies
You would get functional MRI scans to map brain activity and have your DBS device settings and clinical responses recorded. Researchers will apply deep learning (AI) to the imaging and outcome data to predict better stimulation parameters. The work targets both older four-contact DBS leads and newer multi-contact directional leads so stimulation can hit smaller brain areas and avoid side effects. The aim is to shorten the months-long trial-and-error tuning process, reduce clinic visits, and improve symptom control.
Why it matters
Potential benefit: If successful, this could cut the time and number of visits needed to find effective DBS settings and reduce stimulation-related side effects.
How similar studies have gone: Some prior imaging- and AI-based approaches to guide DBS programming have shown promise, but combining functional MRI with deep learning for routine clinical tuning is relatively new.
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.