Decoding natural signals from the peripheral retina

Ganglion cells in the peripheral retina have lower density and larger receptive fields than in the fovea. Consequently, the visual signals relayed from the periphery have substantially lower resolution than those relayed by the fovea. The information contained in peripheral ganglion cell responses can be quantified by how well they predict the foveal ganglion cell responses to the same stimulus. We constructed a model of human ganglion cell outputs by combining existing measurements of the optical transfer function with the receptive field properties and sampling densities of midget (P) ganglion cells. We then simulated a spatial population of P-cell responses to image patches sampled from a large collection of luminance-calibrated natural images. Finally, we characterized the population response to each image patch, at each eccentricity, with two parameters of the spatial power spectrum of the responses: the average response contrast (standard deviation of the response patch) and the falloff in power with spatial frequency. The primary finding is that the optimal estimate of response contrast in the fovea is dependent on both the response contrast and the steepness of the falloff observed in the periphery. Humans could exploit this information when decoding peripheral signals to estimate contrasts, estimate blur levels, or select the most informative locations for saccadic eye movements.