Neurobiologically realistic model of statistical pooling in peripheral vision

Our senses can process only a limited amount of the incoming sensory information. In the human visual system this becomes apparent in the reduced performance in the peripheral field of view, as compared to the central fovea. Recent research shows that this loss of information cannot solely be attributed to a spatially coarser resolution but is essentially caused by statistical pooling operations which lead to a texture-like representation. This so called “crowding effect” can be seen as a strategy of the visual system to deal with the information bottleneck in sensory processing. As such, it may also be of interest for image compression, feature extraction and computer vision. A recent approach towards modelling this effect makes direct use of formal statistical computations [Balas et al. 2009; Freeman and Simoncelli 2011], and thus is not completely convincing with respect to its neurobiological plausibility. Here we investigate whether a more plausible model can be developed and whether it achieves the desirable properties.