Identifying behavioral signs to predict seizures and mortality in epilepsy
Official title: Behavioral biomarkers for prediction of mortality and seizures in epilepsy
Funded at Stanford University · NIH-11050529 · Data updated 2026-11-12
This study is looking for new ways to predict seizures and improve treatment for people with epilepsy by using smart technology to analyze mouse behaviors, which could help us better understand the condition and how it affects individuals.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | December 1, 2024 |
| Project end | November 30, 2029 |
| Funding year | 2025 |
| Award (this year) | $555,499 |
| NIH project number | 1R01NS136355-01A1 |
| Project ID | NIH-11050529 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals of all ages with epilepsy, particularly those who experience treatment-resistant seizures.
✕Less likely to help
Patients who do not have epilepsy or those whose seizures are well-controlled with current treatments may not benefit from this research.
What this research studies
This research focuses on developing innovative biomarkers to predict seizures and mortality in individuals with epilepsy. By utilizing advanced artificial intelligence techniques and 3D video analysis, the study aims to analyze mouse behaviors to differentiate between epileptic and non-epileptic conditions. The goal is to create non-invasive methods that can monitor and predict seizure activity, ultimately improving treatment strategies for epilepsy. This approach could lead to significant advancements in understanding how epilepsy develops and progresses.
Why it matters
Potential benefit: If successful, this research could lead to better prediction and management of seizures, potentially reducing mortality rates in patients with epilepsy.
How similar studies have gone: Previous research using AI-assisted behavioral analysis has shown promise in identifying seizure patterns, suggesting that this approach could yield valuable insights.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Soltesz, Ivan — Stanford University
- Study coordinator: Soltesz, Ivan
Related research
Other NIH-funded projects on the same topics.
-
Predicting seizure patterns in focal epilepsy patients
Aims to create personalized models to forecast how often seizures will happen over time in people with focal epilepsy.
-
Behavior-based signs to predict seizures and death risk in epilepsy
Researchers are using AI-driven 3D video analysis of mouse behaviors to find subtle behavior patterns that might signal seizure risk and higher mortality for people with epilepsy.
-
Predicting seizure patterns for people with focal epilepsy
This project builds tools to forecast how often seizures may happen over time for people with focal epilepsy using long-term seizure records.
-
Investigating a new treatment for seizures using a specific inhibitor in mice
This study is looking at how a special treatment might help reduce seizures in mice with epilepsy, especially when the condition starts after injuries like strokes or head trauma, and it uses a method that could be easier and safer than current treatments.
-
Investigating how to predict epilepsy in newborns with seizures
This study is looking at the best medications to help newborns who have seizures, which can sometimes lead to bigger health issues later on, and it's for families with babies who might be experiencing these seizures.
-
How mild traumatic brain injuries affect brain function and seizures in veterans with epilepsy
This study is looking at how mild traumatic brain injuries can affect brain function and lead to epilepsy in veterans, and it aims to find new ways to help improve their symptoms and overall quality of life.
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.