On Markov blankets and hierarchical self-organisation

JOURNAL OF THEORETICAL BIOLOGY

卷:486

Article

Palacios, Ensor Rafael¹  Razi, Adeel^1,2,3,4  Parr, Thomas¹  Kirchhoff, Michael⁵  Friston, Karl¹ 

[1] UCL, Wellcome Ctr Human Neuroimaging, Queen Sq, London WC1N 3BG, England

[2] Monash Univ, Monash Inst Cognit & Clin Neurosci, Clayton, Vic, Australia

[3] Monash Univ, Monash Biomed Imaging, Clayton, Vic, Australia

[4] NED Univ Engn & Technol, Dept Elect Engn, Karachi, Pakistan

[5] Univ Wollongong, Fac Law Humanities & Arts, Dept Philosophy, Wollongong, NSW 2500, Australia

关键词: Self-organisation;    Markov blanket;    Dynamical systems;    Free energy;    Active inference;   

DOI  :  10.1016/j.jtbi.2019.110089

来源: Elsevier

【 摘 要 】

Biological self-organisation can be regarded as a process of spontaneous pattern formation; namely, the emergence of structures that distinguish themselves from their environment. This process can occur at nested spatial scales: from the microscopic (e.g., the emergence of cells) to the macroscopic (e.g. the emergence of organisms). In this paper, we pursue the idea that Markov blankets - that separate the internal states of a structure from external states - can self-assemble at successively higher levels of organisation. Using simulations, based on the principle of variational free energy minimisation, we show that hierarchical self-organisation emerges when the microscopic elements of an ensemble have prior (e.g., genetic) beliefs that they participate in a macroscopic Markov blanket: i.e., they can only influence - or be influenced by - a subset of other elements. Furthermore, the emergent structures look very much like those found in nature (e.g., cells or organelles), when influences are mediated by short range signalling. These simulations are offered as a proof of concept that hierarchical self-organisation of Markov blankets (into Markov blankets) can explain the self-evidencing, autopoietic behaviour of biological systems. (C) 2019 Elsevier Ltd. All rights reserved.

【 授权许可】

Free