Induced motion at texture–defined motion boundaries

Abstract

When a static textured background is covered and uncovered by a moving bar of the same mean luminance we can clearly see the motion of the bar. Texture-de¢ned motion provides an example of a naturally occurring second-order motion. Second-order motion sequences defeat standard spatio-temporal energy models of motion perception. It has been proposed that second-order stimuli are analysed by separate systems, operating in parallel with luminance-de¢ned motion processing, which incorporate identi¢able pre-processing stages that make second-order patterns visible to standard techniques. However, the proposal of multiple paths to motion analysis remains controversial. Here we describe the behaviour of a model that recovers both luminance-de¢ned and an important class of texture-de¢ned motion. The model also accounts for the induced motion that is seen in some texture-de¢ned motion sequences. We measured the perceived direction and speed of both the contrast envelope and induced motion in the case of a contrast modulation of static noise textures. Signi¢cantly, the model predicts the perceived speed of the induced motion seen at second-order texture boundaries. The induced motion investigated here appears distinct from classical induced e¡ects resulting from motion contrast or the movement of a reference frame.

Engaging with computer science through magic shows

“…This naturally leads to an investigation of what kinds of rules exist in the brain and so to a discussion of approaches to Artificial Intelligence that copy the biological machinery, such as neural networks. This can then help motivate links to vision research, where illusions are used to help understand brain function and validate computer modeling, a useful example being a computer model that has predicted new optical illusions [10].…”

Exploring the spatiotemporal properties of fractal rotation perception

“…As such, several models integrating such nonlinear transformation have been proposed. Full-and half-wave rectification (Chubb & Sperling, 1988, 1991Solomon & Sperling, 1994), filter-rectify-filter (Wilson et al, 1992), and spatiotemporal gradient Benton, Johnston, & McOwan, 2000;Johnston, Benton, & McOwan, 1999) all constitute examples of models using nonlinear transformation to extract second-order motion signal.…”

Moving from spatially segregated to transparent motion: a modelling approach

“…The McGM is a biologically plausible model that has been successful in predicting perceived motion in a range of studies ( Johnston & Clifford 1995a;Johnston & Clifford 1995b;Johnston et al 1999b) and which produces a readily analysable velocity histogram. We assume that the output from the model represents a spatial map of the neural response in area MT of primates.…”