Inverse Bayesian inference as a key of consciousness featuring a macroscopic quantum logical structure

Yukio Gunji, Shuji Shinohara, Taichi Haruna, Vasileios Basios

    Research output: Contribution to journalArticle

    15 Citations (Scopus)

    Abstract

    To overcome the dualism between mind and matter and to implement consciousness in science, a physical entity has to be embedded with a measurement process. Although quantum mechanics have been regarded as a candidate for implementing consciousness, nature at its macroscopic level is inconsistent with quantum mechanics. We propose a measurement-oriented inference system comprising Bayesian and inverse Bayesian inferences. While Bayesian inference contracts probability space, the newly defined inverse one relaxes the space. These two inferences allow an agent to make a decision corresponding to an immediate change in their environment. They generate a particular pattern of joint probability for data and hypotheses, comprising multiple diagonal and noisy matrices. This is expressed as a nondistributive orthomodular lattice equivalent to quantum logic. We also show that an orthomodular lattice can reveal information generated by inverse syllogism as well as the solutions to the frame and symbol-grounding problems. Our model is the first to connect macroscopic cognitive processes with the mathematical structure of quantum mechanics with no additional assumptions.

    Original languageEnglish
    Pages (from-to)44-65
    Number of pages22
    JournalBioSystems
    Volume152
    DOIs
    Publication statusPublished - 2017 Feb 1

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    ASJC Scopus subject areas

    • Statistics and Probability
    • Modelling and Simulation
    • Biochemistry, Genetics and Molecular Biology(all)
    • Applied Mathematics

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