Modelling and simulation of spontaneous perception switching with ambiguous visual stimuli in augmented vision systems

A behavioral nonlinear dynamics model of multistable perception due to ambiguous visual stimuli is presented. The perception state is formalized as the dynamic phase variable v(t) of a recursive process with cosinuidal transfer characteristic which is created by superposition (interference) of neuronal mean fields. The two parameters mu = difference of meaning of alternative percepts and G = attention parameter, control the transition between unambiguous and ambiguous stimuli, e.g. from stimulus off to stimulus on, and attention fatigue respectively. Mean field interference with delayed phase feedback enables transitions between chaotic and limit cycle attractors v(t) representing the perception states. Perceptual reversals are induced by attention fatigue G(t) (similar to adaptive gain g(v)) with time constant gamma, and attention bias which determines the relative duration of the percepts. The coupled attention - perception dynamics with an additive stochastic noise term reproduces the experimentally observed F-distribution of the reversal time statistics. Mean reversal times of typically 3 - 5 s as reported in the literature, are correctly predicted if delay T is associated with the delay of 40 ms between stimulus onset and primary visual cortex (VI) response. Numerically determined perceptual transition times of 3 - 5 T are in reasonable agreement with stimulus - conscious perception delay of 150 - 200 ins [11]. Eigenfrequencies of the limit cycle oscillations are in the range of 10 - 100 Hz, in agreement with typical EEG frequencies.