2026 Lecture
AI-derived Mechanisms of Human Vision
Monday, March 30, 2026, 4 pm
Staller Center Main Stage
Livestreamed at stonybrook.edu/live
Over the past decade, neuroscience, cognitive science and computer science (“AI”)
converged to create deep neural network models intended to appropriately emulate and
explain the mechanisms of primate core ventral visual processing, up to its deepest
neural level, the inferior temporal cortex (IT). Because these leading neuroscientific
emulator models — aka “digital twins” — are fully observable and machine-executable,
they offer predictive and potential application power that prior conceptual models
did not.
Dr. James DiCarlo’s work is aimed at asking if current digital twin models might support
non-invasive, beneficial brain modulation. In this talk, he will discuss how a digital twin can be used to design spatial patterns
of light energy that, when added to an organism’s retinal input, result in precise,
user-selectable modulation of the pattern of a population of IT neurons.