Retinal input

Over the past decade, neuroscience, cognitive science and computer science (“AI”) converged to create specific, image-computable, deep neural network models intended to appropriately abstract, emulate and explain the mechanisms of primate ventral visual processing, up to its deepest neural level, the inferior temporal cortex (IT). Because these leading neuroscientific emulation models — aka “digital twins” — are fully observable and machine-executable, they offer predictive and potential application power that our field’s prior conceptual models did not. Our team’s ongoing work is aimed at ask

…To address this, we analyzed the retinal input encountered during free exploration by measuring the mouse’s visual scene (“worldcam”) and eye/head position using head-mounted cameras and an inertial measurement unit (IMU). Based on these measures, we trained a neural network to estimate the retinal input by gaze-correcting the worldcam