Our visual system's ability to group visual elements into meaningful entities and to separate them from others is referred to as scene segmentation. Visual motion often provides a powerful cue for this process as parallax or coherence can inform the visual system about scene or object structure. Here we tested the hypothesis that scene segmentation by motion cues relies on a common neural substrate in the parietal cortex. We used fMRI and a set of three entirely distinct motion stimuli to examine scene segmentation in the human brain. The stimuli covered a wide range of high-level processes, including perceptual grouping, transparent motion, and depth perception. All stimuli were perceptually bistable such that percepts alternated every few seconds while the physical stimulation remained constant. The perceptual states were asymmetric, in that one reflected the default (nonsegmented) interpretation, and the other the non-default (segmented) interpretation. We confirmed behaviorally that upon stimulus presentation, the default percept was always perceived first, before perceptual alternations ensued. Imaging results showed that across all stimulus classes perceptual scene-segmentation was associated with an increase of activity in the posterior parietal cortex together with a decrease of neural signal in the early visual cortex. This pattern of activation is compatible with predictive coding models of visual perception, and suggests that parietal cortex hosts a generic mechanism for scene segmentation. Making sense of cluttered visual scenes is crucial for everyday perception. An important cue to scene segmentation is visual motion: slight movements of scene elements give away which elements belong to the foreground or background or to the same object. We used three distinct stimuli that engage visual scene segmentation mechanisms based on motion. They involved perceptual grouping, transparent motion, and depth perception. Brain activity associated with all three mechanisms converged in the same parietal region with concurrent deactivation of early visual areas. The results suggest that posterior parietal cortex is a hub involved in structuring visual scenes based on different motion cues, and that feedback modulates early cortical processing in accord with predictive coding theory.

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Magic tricks have enjoyed an increasing interest by scientists. However, most research in magic focused on isolated aspects of it and a conceptual understanding of magic, encompassing its distinct components and varieties, is missing. Here, we present an account of magic within the theory of Bayesian predictive coding. We present the "wow" effect of magic as an increase in surprise evoked by the prediction error between expected and observed sensory data. We take into account prior knowledge of the observer, attention, and (mis-)direction of perception and beliefs by the magician to bias the observer's predictions and present two examples for the modelling of the evoked surprise. The role of misdirection is described as everything that aims to maximize the surprise a trick evokes by the generation of novel beliefs, the exploitation of background knowledge and attentional control of the incoming information. Understanding magic within Bayesian predictive coding allows unifying all aspects of magic tricks within one framework, making it tractable, comparable and unifiable with other models in psychology and neuroscience.

Editor's Note: These short, critical reviews of recent papers in the Journal, written exclusively by graduate students or postdoctoral fellows, are intended to summarize the important findings of the paper and provide additional insight and commentary. For more information on the format and purpose of the Journal Club, please see http://www.jneurosci.org/misc/ifa_features.shtml.

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