Eshed Margalit

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Abstract Ever-advancing artificial neural network (ANN) models of the ventral visual stream capture core object recognition behavior and the neural mechanisms underlying it with increasing precision. These models take images as input, propagate through simulated neural representations that resemble biological neural representations at all stages of the primate ventral stream, and produce simulated behavioral choices that resemble primate behavioral choices.

Abstract Human visual cortex is organized into dorsal, lateral, and ventral streams. A long-standing hypothesis is that the functional organization into streams emerged to support distinct visual behaviors. Here, we use a neural network-based computational model and a massive fMRI dataset to test how visual streams emerge. We find that models trained for stream-specific visual behaviors poorly capture neural responses and organization.