When Scenes Look Like Materials: René Magritte’s Reversible Figure–Ground Motif

We draw attention to a frequent motif in the work of the Belgian surrealist René Magritte (1898–1967). In the motif, a scene is depicted that contains a silhouette, which itself contains another depicted scene. The silhouette is bistable, appearing either as a figural region whose positive space is covered, or filled, with the interior scene texture, or as a ground region providing a window onto a more distant scene. We call this the ‘reversible figure–ground motif’. Because the stimulus does not change when our percept changes, the motif’s appearance at any particular moment cannot be explained by its local or global image statistics. Instead principles of perceptual organization, and in particular image segmentation and figure–ground assignment, appear crucial for determining whether the interior of the silhouette is processed as a material vs. a scene — which in turn reflects the fundamental role of visual segmentation in material and scene perception more generally.

Threshold Differences on Figure and Ground: Gelb and Granit (1923)

In 1923, Gelb and Granit, using a method of adjustment for a small red light, reported a lower threshold for the target when presented on a ground region than on an adjacent figural region. More recent work in perceptual organization has found precisely the opposite—a processing advantage seems to go to items presented on the figure, not the ground. Although Gelb and Granit continue to be cited for their finding, it has not previously been available as an English translation. Understanding their methodology and results is important for integrating early Gestalt theory with more recent investigations.

Figure—Ground Segregation in a Recurrent Network Architecture

Here we propose a model of how the visual brain segregates textured scenes into figures and background. During texture segregation, locations where the properties of texture elements change abruptly are assigned to boundaries, whereas image regions that are relatively homogeneous are grouped together. Boundary detection and grouping of image regions require different connection schemes, which are accommodated in a single network architecture by implementing them in different layers. As a result, all units carry signals related to boundary detection as well as grouping of image regions, in accordance with cortical physiology. Boundaries yield an early enhancement of network responses, but at a later point, an entire figural region is grouped together, because units that respond to it are labeled with enhanced activity. The model predicts which image regions are preferentially perceived as figure or as background and reproduces the spatio-temporal profile of neuronal activity in the visual cortex during texture segregation in intact animals, as well as in animals with cortical lesions.