The bayesian causal inference in multisensory information processing: A narrative review

Abstract

When processing the simultaneous multisensory information, the brain must first infer whether the information comes from the same object, which is a prerequisite for multisensory information processing. The Bayesian causal inference can effectively simulate the inference process in the brain and predict the results. This paper reviews the research of multisensory information processing based on Bayesian causal inference, introduces the Bayesian causal inference theory in multisensory information processing, explains the multisensory information processing based on this theory in detail, analyzed the factors influencing the causal inference and the future research direction, in order to enhance the new understanding of the brain-like model for multisensory information processing, and to provide reference for the research of multisensory information processing in future.