Abstract
AbstractWe have recently shown that using the information carried by the mosaic of cone excitations of a stationary retina, the relative spatial contrast sensitivity function (CSF) of a computational observer has the same shape as a typical human subject. Absolute human sensitivity, however, is lower than the computational observer by a factor of 5 to 10. Here we model how additional known features of early vision affect spatial contrast sensitivity: fixational eye movements and the conversion of cone photopigment excitations to cone photocurrent responses. 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 spatial CSF, primarily by reducing sensitivity at spatial frequencies above 10 c/deg. For a computational observer that uses a translation-invariant calculation, in which decisions are based 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. The noise and response dynamics of conversion of cone excitations into photocurrent introduce an additional two-fold sensitivity decrease. Hence, the combined effects of fixational eye movements and phototransduction bring the absolute sensitivity of the translation-invariant computational observer CSF to within a factor of 1 to 2 of the human CSF. We note that the human CSF depends on processing of the initial representation by many thalamic and cortical neurons, which are individually quite noisy. Our computational modeling suggests that the net effect of this noise on contrast-detection performance, when considered at the neural population level and behavioral level, is quite small: the inference mechanisms that determine the CSF, presumably in cortex, make efficient use of the information available from the cone photocurrents of the fixating eye.
Publisher
Cold Spring Harbor Laboratory
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