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At the most general level, multisensory integration (or multisensor data fusion) in application contexts is best described in terms of Bayesian theory, its specializations, and approximations to it.

Bayesian models cannot explain why natural cognition is not always optimal or predict bahavior in cases when it is not.

Already von Helmholtz formulated the idea that prior knowledge---or expectations---are fused with sensory information into perception.

This idea is at the core of Bayesian theory.

`Fundamentalist Bayesians' posit that they can predict behavior purely on the basis of optimality.

Jones and Love talk about Bayesian theory as psychological theories---not so much as neuroscientific theories... I guess?