Understanding how the brain perceives 3D objects
Official title: "CRCNS": Brain-derived network architectures for deciphering and applying brain algorithms
Funded at Johns Hopkins University · NIH-11081826 · Data updated 2026-11-12
This study is exploring how our brains understand 3D images, like how we see shapes and movements, by using advanced computer programs that mimic brain functions, and it’s based on research with macaque monkeys to help improve both natural and artificial vision.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | August 1, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $409,375 |
| NIH project number | 1R01EY037193-01 |
| Project ID | NIH-11081826 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research include individuals with visual perception disorders or those interested in advancements in artificial vision technologies.
✕Less likely to help
Patients with conditions unrelated to visual perception or those not engaged in fields utilizing 3D vision technologies may not receive direct benefits from this research.
What this research studies
This research aims to enhance our understanding of how the brain processes three-dimensional (3D) visual information, moving beyond traditional 2D image recognition. By utilizing advanced artificial vision networks, the study will analyze how specific brain algorithms contribute to our perception of 3D structures, including their geometry, material properties, and potential movements. The research involves training these networks using data from macaque monkeys to replicate the brain's 3D shape processing capabilities. This innovative approach could lead to breakthroughs in both biological and artificial vision systems.
Why it matters
Potential benefit: If successful, this research could significantly improve technologies related to visual recognition and understanding, benefiting fields such as robotics, virtual reality, and medical imaging.
How similar studies have gone: Previous research in biological and artificial vision has shown promising results in understanding 2D image recognition, but this approach to 3D perception is relatively novel.
Where this research is happening
-
Johns Hopkins University
Baltimore, United States Active
Researchers
- Principal investigator: Connor, Charles E — Johns Hopkins University
- Study coordinator: Connor, Charles E
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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.