Information theory is used to predict an optimal spatial distribution of a given number of photodetectors. We compare our results with the known distribution in the human eye. The optimization takes into account eye movement which leads to different optimal arrays depending on the time scales of the visual information. When the visual data contains mixed time scales, maximum information flow is achieved by an array distribution consisting of both a large uniform low resolution region, and a smaller high resolution region, as in the human retina. Optimal ratios of areas and densities of these two regions are calculated as a function of the number of eye movements. The results lend support to the hypothesis that the retina is an information theoretically optimal processor.
"Optimal spatial distribution of photodetector array using information theory", Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140087; https://doi.org/10.1117/12.140087