Bioplausible multiscale filtering in retino-cortical processing as a mechanism in perceptual grouping

Polarity-dependent orientation illusions: Review, model, and simulations

Polarity-dependent orientation illusions are manifested in figures in which the impression of target orientation does not depend only on geometrical relations between the elements of the figure, but also on the relations between their luminances, that is, on luminance polarities. The best-known phenomenon belonging to this class of effects is the Münsterberg/Café Wall illusion. In this paper a considerable number of examples of this type of illusions are presented, many of which are novel variants. A two-level convolutional model of such illusions is introduced, in which the first level corresponds to the stimulus input and the second level contains units fashioned after simple cells in V1, whose spatial patterns of activity represent the model's reaction to the stimulus. The main finding of numerous simulations of the model is that the figures inducing illusory impressions of tilt share a common spatial pattern of neural activation, labeled 'oblique clusters', which is absent in related non-illusory figures. Furthermore, a similar pattern is also present in simulations of figures which induce veridical impressions of tilt. The simulations suggest that the neural basis of perception of a specific degree of tilt may not be the activity of neurons tuned narrowly to that particular degree of tilt, but rather the presence of certain signature spatial patterns of activity of populations of neurons.

The Café Wall Illusion: Local and Global Perception from Multiple Scales to Multiscale

Geometrical illusions are a subclass of optical illusions in which the geometrical characteristics of patterns in particular orientations and angles are distorted and misperceived as a result of low-to-high-level retinal/cortical processing. Modelling the detection of tilt in these illusions, and its strength, is a challenging task and leads to the development of techniques that explain important features of human perception. We present here a predictive and quantitative approach for modelling foveal and peripheral vision for the induced tilt in the Café Wall illusion, in which parallel mortar lines between shifted rows of black and white tiles appear to converge and diverge. Difference of Gaussians is used to define a bioderived filtering model for the responses of retinal simple cells to the stimulus, while an analytical processing pipeline is developed to quantify the angle of tilt in the model and develop confidence intervals around them. Several sampling sizes and aspect ratios are explored to model variant foveal views, and a variety of pattern configurations are tested to model variant Gestalt views. The analysis of our model across this range of test configurations presents a precisely quantified comparison contrasting local tilt detection in the foveal sample sets with pattern-wide Gestalt tilt.