title: Bistable perception modeled as competing stochastic integrations at two levels.
abstract: We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.
authors: Wolf Soluzioni, Rome, Italy. guido.gigante@iss.infn.it
authors: Guido
authors: G
authors: Gigante
authors: Maurizio
authors: M
authors: Mattia
authors: Jochen
authors: J
authors: Braun
authors: Paolo
authors: P
authors: Del Giudice
mesh_terms: D000465:Algorithms; D008959:Models, Neurological; D010465:Perception / Q000502:physiology*; D010775:Photic Stimulation; D013269:Stochastic Processes; D013997:Time Factors; D015348:Vision, Binocular / Q000502:physiology*