1. From: Vision and touch are automatically integrated for the perception of sequences of events
Journal of Vision. 2006;6(5):2. doi: /6.5.2
Figure Legend:
Bayesian model for sensory integration. The perceptual interaction between the sensory signals can be described using the Bayesian approach (Ernst, 2005). In the figure, the likelihood function has its maximum at (î,ĵ) and the standard deviation of the bivariate Gaussian distribution is (σi,σj). Thus, it represents the perceptual estimate when both signals are presented separately. The covariance is assumed to be 0 in this example. The prior represents the mapping between the signals and is thus aligned with the identity line where i = j. The variance of this prior (σp2), which is assumed to be Gaussian distributed, represents the uncertainty in the mapping. Using Bayes' formula, the posterior is calculated by multiplying the likelihood with the prior distribution (and normalizing it).
Date of download: 10/3/2017
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