title: Slow dynamics perspectives on the Embodied-Brain Systems Science.
abstract: Recent researches point out the importance of the fast-slow cognitive process and learning process of self-body. Bayesian perspectives on the cognitive system also attract research attentions. The view of fast-slow dynamical system has long attracted wide range of attentions from physics to the neurobiology. In many research fields, there is a vast well-organized and coherent behavior in the multi degrees-of-freedom. This behavior matches the mathematical fact that fast-slow system is essentially described with a few variables. In this paper, we review the mathematical basis for understanding the fast-slow dynamical systems. Additionally, we review the basis of Bayesian statistics and provide a fast-slow perspective on the Bayesian inference.
authors.affiliation: Department of Computer and Information Sciences, Tokyo University of Agriculture and Technology, 2-24-16 Nakachou, Koganei-shi, Tokyo 184-8588, Japan. Electronic address: syano@cc.tuat.ac.jp.
authors.forename: Shiro
authors.initials: S
authors.lastname: Yano
authors.affiliation: Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan. Electronic address: takaki@xa3.so-net.ne.jp.
authors.forename: Takaki
authors.initials: T
authors.lastname: Maeda
authors.affiliation: Department of Computer and Information Sciences, Tokyo University of Agriculture and Technology, 2-24-16 Nakachou, Koganei-shi, Tokyo 184-8588, Japan. Electronic address: t_kondo@cc.tuat.ac.jp.
authors.forename: Toshiyuki
authors.initials: T
authors.lastname: Kondo
mesh_terms: D001499:Bayes Theorem; D001828:Body Image; D001921:Brain / Q000502:physiology*; D003071:Cognition / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology
keywords: Bayesian statistics; Dimension reduction; Dynamical system; Embodied-Brain Systems Science; Fast-slow systems; Statistical learning theory