摘要：In this paper, we review the nature of illusions using the free-energy formulation of Bayesian perception. We reiterate the notion that illusory percepts are, in fact, Bayes-optimal and represent the most likely explanation for ambiguous sensory input. This point is illustrated using perhaps the simplest of visual illusions; namely, the Cornsweet effect. By using plausible prior beliefs about the spatial gradients of luminance and reflectance in the visual world, we show that the Cornsweet effect emerges as a natural consequence of Bayes-optimal perception. Furthermore, we were able to simulate the appearance of secondary illusory percepts (Mach bands) as a function of stimulus contrast. The contrast-dependent emergence of the Cornsweet effect and subsequent appearance of Mach bands were simulated using a simple but plausible generative model. We verified the qualitative and quantitative predictions of this model psychophysically, using briefly presented stimuli at different contrast levels and a fixed alternative forced choice paradigm. Because our generative model was inverted using a neurobiologically plausible scheme based on generalised predictive coding, we could use the inversion as a simulation of neuronal inference and processing. This allowed us to simulate event related potentials. We hope to use this inversion scheme as a model of empirical electromagnetic responses in future work; to associate the functional architecture of the generative model with neuronal responses in visual cortex.
