What is the goal of neural image processing in the retina?

Abstract

Vision scientists since Helmholtz have argued that human visual perception is best understood as an inference process that seeks to explain the physical causes of the retinal image. Photographers know very well that the task of image acquisition itself is intrinsically tied to this process of image interpretation. For a similar reason, it is important to our understanding of the retina that we can say how the generation of nerve impulses is shaped by the task of image interpretation. The redundancy reduction hypothesis put forth by Barlow is an attempt to turn this kind of thoughts into mathematical models that can offer a computational interpretation of neural response properties observed experimentally. While many studies have investigated how neural filter properties may be shaped by the spatial statistics of natural images, the temporal properties of the retinal sampling process have mostly been ignored. Here, we study the spatio- temporal statistics of temporal sequences of images that are obtained when a static scene is dynamically sampled with saccadic gaze shifts and fixational eye movements. We present new analytic results which explain the effect of the dynamic sampling process on the spatio-temporal correlation function of the visual input. Based on these results, we will speculate about possible implications for neural image coding in the retina