Deterministic Chaos Approach to Multistable Perception

Multistable perception is perception in which two (or more) interpretations of the same ambiguous image alternate while an obserber looks at them. Perception undergoes involuntary and random-like change. The question arises whether the apparent randomness of alternation is real (that is, due to a stochastic process) or whether any underlying deterministic structure to it exists. In this paper, we examine the spatially coherent temporal behaviors of multistable perception model based on the chaotic neural network from the viewpoint of bottom-up high dimensional approach, aiming at the functioning of chaos in dynamic perceptual processes.