Understanding how the retina processes information with advanced AI models
Official title: CRCNS Research Proposal: Optimal Information processing via cell types
Funded at New York University · NIH-11538397 · Data updated 2026-11-12
A NIH-funded project uses smart computer models to explain why the human retina has many cell types and how they help vision.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York University NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 30, 2026 |
| Project end | September 29, 2030 |
| Funding year | 2026 |
| Award (this year) | $1,220,425 |
| NIH project number | 1R01EY040100-01 |
| Project ID | NIH-11538397 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not a patient-facing study; this is a basic science project using retinal data and animal/arena measurements.
✕Less likely to help
There is no direct patient trial or treatment in this grant.
What this research studies
Researchers at New York University will use modern machine learning to build flexible models of retinal information processing. By comparing model predictions with measurements from primate and squirrel retinas, they aim to connect general information-processing principles with the function of specific retinal cell types. The work looks at color channels, realistic noise, and the diverse retinal cell mosaic to uncover why the eye is so complex yet efficient at vision.
Why it matters
Potential benefit: If successful, this work could deepen our understanding of vision and guide future therapies or artificial vision technologies.
How similar studies have gone: Previous EC-based retina models captured only a subset of cell-type diversity; this project aims to expand that understanding with more realistic modeling.
Where this research is happening
-
New York University
New York, United States Active
Researchers
- Principal investigator: Pearson, John — New York University
- Study coordinator: Pearson, John
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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.