Understanding animal behavior through advanced monitoring techniques
Official title: Behavioral quantification through active learning and multidimensional physiological monitoring
Funded at Carnegie-Mellon University · NIH-10786800 · Data updated 2026-11-12
This study is looking at how mice behave in different situations by using advanced technology to track their movements and sounds, and it also wants to understand how their gut health affects their reactions to their surroundings.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Carnegie-Mellon University NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project start | August 1, 2024 |
| Project end | July 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $331,381 |
| NIH project number | 1R34DA059509-01 |
| Project ID | NIH-10786800 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research would include researchers and clinicians interested in behavioral science and animal models.
✕Less likely to help
Patients who are not involved in behavioral research or do not have an interest in animal models may not receive any benefit from this research.
What this research studies
This research investigates how animals respond to their environment by analyzing their behavior using innovative machine learning techniques. By monitoring various physiological signals and behaviors in mice, such as body position and vocalizations, the study aims to create a detailed toolkit for quantifying complex behaviors. The research will also explore the influence of the gut-brain axis on these behaviors in response to specific environmental challenges. This comprehensive approach will help validate new analytical methods and provide insights into animal behavior.
Why it matters
Potential benefit: If successful, this research could enhance our understanding of animal behavior, leading to better models for studying human psychological and physiological responses.
How similar studies have gone: Other research has shown success in using machine learning for behavioral analysis, indicating that this approach has potential for significant advancements.
Where this research is happening
-
Carnegie-Mellon University
Pittsburgh, United States Active
Researchers
- Principal investigator: Yttri, Eric — Carnegie-Mellon University
- Study coordinator: Yttri, Eric
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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.