How does our brain turn limited sensory data into a rich visual experience? In this episode, we sit down with Dr. David Brainard, a professor of psychology at the University of Pennsylvania, to dive deep into the world of visual perception, inference, and computational modeling.
Dr. Brainard shares his journey from physics to psychology and explains how his research explores how the brain processes light, interprets color, and makes inferences about the world around us. We also discuss his work in computational modeling, which is transforming our understanding of retinal function, neural efficiency, and AI-driven vision systems. From cutting-edge research to the future of brain-computer interfaces and neurodegenerative treatments, this episode is packed with fascinating insights into how we see and how AI is learning to see.
Timestamps:
00:01 – Introduction to David Brainard and his background in cognitive neuroscience and vision research.
01:50 – How he transitioned from physics to psychology and what drew him to perception research.
02:59 – The role of inference in vision science: how the brain interprets limited sensory information.
05:26 – The importance of computational modeling in understanding how the brain processes vision.
06:56 – Discovering light-sensitive cells and their role in circadian rhythms and pupil response.
09:56 – How light influences sleep, mood, and biological processes beyond just vision.
14:32 – How different retinal cells contribute to visual performance and perception.
16:34 – Using computational models to diagnose retinal diseases and improve treatments.
20:10 – Future applications of vision research: neurodegenerative disease, AI, and BCI.
32:26 – Closing thoughts on academia, research curiosity, and communicating science effectively.