Normative theory of visual receptive fields
This foundational theory addresses the problem of understanding visual processing mechanisms for researchers in computational neuroscience and computer vision, though it appears incremental as it builds on existing normative approaches.
The paper tackles the problem of deriving idealized models of visual receptive fields by proposing a normative computational theory based on environmental structures and vision system assumptions, resulting in predictions that show qualitatively good similarity to biological receptive fields in mammalian retina, LGN, and V1.
This article gives an overview of a normative computational theory of visual receptive fields, by which idealized functional models of early spatial, spatio-chromatic and spatio-temporal receptive fields can be derived in an axiomatic way based on structural properties of the environment in combination with assumptions about the internal structure of a vision system to guarantee consistent handling of image representations over multiple spatial and temporal scales. Interestingly, this theory leads to predictions about visual receptive field shapes with qualitatively very good similarity to biological receptive fields measured in the retina, the LGN and the primary visual cortex (V1) of mammals.