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The Bayesian Causal Inference in Multisensory Information Processing: A Narrative Review

  • Yang Xi
  • Ning Gao
  • Mengchao Zhang
  • Lin Liu
  • Qi Li
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 109)

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.

Keywords

Multisensory integration Causal inference Bayesian causal inference 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yang Xi
    • 1
    • 2
  • Ning Gao
    • 1
  • Mengchao Zhang
    • 3
  • Lin Liu
    • 3
  • Qi Li
    • 1
  1. 1.School of Computer Science and TechnologyChangchun University of Science and TechnologyChangchunPeople’s Republic of China
  2. 2.College of Information EngineeringNortheast Electric Power UniversityJilinPeople’s Republic of China
  3. 3.Department of RadiologyChina-Japan Union Hospital of Jilin UniversityChangchunPeople’s Republic of China

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