NIH R01 · 2025
"CRCNS": Brain-derived network architectures for deciphering and applying brain algorithms
Our LONG-TERM GOAL is to extend current biological and artificial vision research from a focus on 2D image recognition toward visual understanding of 3D structure in the real world. 3D object perception is the essence of real-world vision, underlying the “thousand words” of information the brain generates about precise object geometry on large and fine scales, structural design, mechanics, material composition, biological morphology and functionality, physical state, pose, mass distribution, balance/support against gravity, potential for movement from passive falling/rolling to self-generated motion and complex interactive behaviors, age, beauty, damage, value, etc. Our first AIM is to use…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.