Understanding the mechanisms that control the dynamics of perceptual switches

Northwestern University, Evanston IL

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Abstract

DESCRIPTION (provided by applicant): Even while viewing a constant visual scene, different objects and organizations come to dominate visual awareness, often spontaneously. These "perceptual switches" that spontaneously activate alternative scene interpretations are important because they allow detection of behaviorally significant information which may not be predictable or initially salient and may exist at any level of organization. The literature on binocular rivalry (a paradigm commonly used to study perceptual switches) suggests that perceptual switches are mediated by multi-stage neural competition involving component processes such as signal transduction, adaptation, inhibitory interactions, stochastic noise, non-linearity (e.g., a threshold), and response synchronization. Collective action of these processes controls perceptual switches, and the current dynamic models provide a plausible computational framework for integrating the component processes. However, research has overlooked some key aspects of perceptual switches. Prominently, no attempts have been made to experimentally measure the component processes to determine how their actual (as opposed to hypothesized) properties predict the dynamics of perceptual switches. Without this knowledge, it would be impossible to specify the sources of the substantial individual differences and plasticity observed in the dynamics of perceptual switches. Further, in spite of growing evidence that multi-level processes are involved, little data exist regarding how neural competition at multiple processing stages interactively controls perceptual switches. Our basic strategy will be to psychophysically and electrophysiologically measure the component processes operating at different processing stages, determine how each component process contributes to perceptual switches, and use this information to revise the current models. The advanced models will predict the dynamics of perceptual switches for each individual on the basis of his or her measured component processes. The results will also specify the sources of the unexplained variability in the dynamics of perceptual switches, including individual differences, plasticity, percept-to-percept variability, and effects of intention. Unusually slow or fast perceptual switches may be associated with disorders characterized by perseveration or distractability. Our results may thus facilitate development of effective treatments by tracing the sources of unusual perceptual dynamics to specific component processes.