A computational observer model of spatial contrast sensitivity: Effects of photocurrent encoding, fixational eye movements, and inference engine

We have recently shown that the relative spatial contrast sensitivity function (CSF) of a computational observer operating on the cone mosaic photopigment excitations of a stationary retina has the same shape as human subjects. Absolute human sensitivity, however, is 5- to 10-fold lower than the computational observer. Here we model how additional known features of early vision affect the CSF: fixational eye movements and the conversion of cone photopigment excitations to cone photocurrents (phototransduction). For a computational observer that uses a linear classifier applied to the responses of a stimulus-matched linear filter, fixational eye movements substantially change the shape of the CSF by reducing sensitivity above 10 c/deg. For a translation-invariant computational observer that operates on the squared response of a quadrature-pair of linear filters, the CSF shape is little changed by eye movements, but there is a two fold reduction in sensitivity. Phototransduction dynamics introduce an additional two fold sensitivity decrease. Hence, the combined effects of fixational eye movements and phototransduction bring the absolute CSF of the translation-invariant computational observer to within a factor of 1 to 2 of the human CSF. We note that the human CSF depends on processing of the retinal representation by many thalamo-cortical neurons, which are individually quite noisy. Our modeling suggests that the net effect of post-retinal noise on contrast-detection performance, when considered at the neural population and behavioral level, is quite small: The inference mechanisms that determine the CSF, presumably in cortex, make efficient use of the information carried by the cone photocurrents of the fixating eye.