Using machine learning to analyze behavior in models of Alzheimer's disease
Official title: Harnessing novel machine learning approaches for behavioral segmentation and brain signal integration in humanized models of Alzheimer's disease
Funded at J. David Gladstone Institutes · NIH-11116747 · Data updated 2026-11-12
This study is looking at how new technology can help us understand the behavior changes in mice that have been specially designed to mimic Alzheimer's disease, with the hope that what we learn will lead to better ways to diagnose and treat the condition in people.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | J. David Gladstone Institutes NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | June 15, 2025 |
| Project end | March 31, 2030 |
| Funding year | 2025 |
| Award (this year) | $817,357 |
| NIH project number | 1R01AG092683-01 |
| Project ID | NIH-11116747 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with early signs of Alzheimer's disease or those at high risk due to genetic factors.
✕Less likely to help
Patients with advanced Alzheimer's disease or those with other forms of dementia may not benefit from this research.
What this research studies
This research investigates how advanced machine learning techniques can be applied to analyze behavioral patterns in humanized models of Alzheimer's disease. By utilizing methods like pose estimation and behavioral segmentation, the study aims to capture and quantify subtle changes in behavior and cognitive functions at a very detailed level. The goal is to understand the interactions between different biological factors contributing to Alzheimer's, using specially developed mouse models that mimic human disease more accurately. Patients may benefit from insights gained through this research, which could lead to improved diagnostic and therapeutic strategies for Alzheimer's disease.
Why it matters
Potential benefit: If successful, this research could lead to better understanding and treatment options for Alzheimer's disease.
How similar studies have gone: Other research has shown promising results using machine learning approaches in behavioral analysis, indicating potential for success in this novel application.
Where this research is happening
-
J. David Gladstone Institutes
San Francisco, United States Active
Researchers
- Principal investigator: Palop, Jorge J — J. David Gladstone Institutes
- Study coordinator: Palop, Jorge J
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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.