Uncovering the circuit mechanisms that shape contextual phenomena
Neurons in visual cortex are sensitive to context. Neural responses to stimuli presented within their classical receptive fields (CRFs) are modulated by the presence of other stimuli – in their CRF and their surrounding extra-classical receptive field (eCRF). While CRF and eCRF phenomena have been extensively studied since the inception of visual neuroscience, the circuit mechanisms that shape them and their role in visual perception are not yet understood. In this talk, I will describe my approach for relating these receptive field phenomena to ecological vision, and through this connection develop theory for how visual statistics shape the structure and function of early visual areas. I will next argue that modeling neural circuits involved in the idiosyncrasies of biological vision can help artificial vision. While this idea seems heterodox in our age of deep multilayer perceptrons achieving state-of-the-art performance on object classification (MLP-Mixer, 2021), I will discuss new work demonstrating that introducing models of recurrent neural circuits into artificial vision promotes new strategies for solving visual tasks that improve performance and explanations of human behavior.