Significance of Natural Scene Statistics in Understanding the Anisotropies of Perceptual Filling-in at the Blind Spot

Abstract

Psychophysical experiments reveal our horizontal preference in perceptual filling-in at the blind spot. On the other hand, tolerance in filling-in exhibit vertical preference. What causes this anisotropy in our perception? Building upon the general notion that the functional properties of the early visual system are shaped by the innate specification as well as the statistics of the environment, we reasoned that the anisotropy in filling-in could be understood in terms of anisotropy in orientation distribution inherent in natural scene statistics. We examined this proposition by investigating filling-in of bar stimuli in a Hierarchical Predictive Coding model network. The model network, trained with natural images, exhibited anisotropic filling-in performance at the blind spot, which is similar to the findings of psychophysical experiments. We suggest that the over-representation of horizontal contours in the natural scene contributes to the observed horizontal superiority in filling-in and the broader distribution of vertical contours contributes to the observed vertical superiority of tolerance in filling-in. These results indicate that natural scene statistics plays a significant role in determining the filling-in performance at the blind spot and shaping the associated anisotropies.