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, vertical preference is exhibited in the case of tolerance in filling-in. 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 to natural scene statistics. We examined this proposition by investigating filling-in of bar stimuli on a Hierarchical Predictive Coding model network. In response to bar stimuli, the model network, trained with natural images, exhibited anisotropic filling-in performance at the blind spot similar to reported in psychophysical experiments i.e. horizontal preference in filling-in and vertical preference in tolerance of filling-in. We suggest that the over-representation of horizontal contours in the natural scene contribute to the observed horizontal superiority while the broader distribution of vertical contours contributes to the observed vertical superiority in tolerance. 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.