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Biological self-organisation and Markov blankets

Other


Type Of Work


  • Other

Abstract


  • Biological self-organisation is a process of spontaneous pattern formation; namely the emergence of coherent and stable systemic configurations that distinguish themselves from their environment. This process can occur at various spatial scales: from the microscopic (giving rise to cells) to the macroscopic (the emergence of organisms). Self-organisation at each level is essential to account for the hierarchical organisation of living organisms (organelles within cells, within tissues, within organs, etc.). In this paper, we pursue the idea that Markov blankets – statistical boundaries separating states that are external to a system from its internal states – emerge at every possible level of the description of the (living) system. Through simulations, we show that the concept of a Markov blanket is fundamental in defining biological systems and underwrites the nature and form of interactions between successive levels of hierarchical structure. We demonstrate the validity of our argument using simulations, based on the normative principle of variational free energy minimisation. Specifically, we adopt a top-down approach to provide a proof of concept for the claim that the self-organisation of Markov blankets (and blankets of blankets) underwrites the self-evidencing, autopoietic behaviour of living systems.

Authors


  •   Palacios, Ensor (external author)
  •   Razi, Adeel (external author)
  •   Parr, Thomas (external author)
  •   Kirchhoff, Michael D.
  •   Friston, Karl (external author)

Publication Date


  • 2017

Citation


  • Palacios, E. Rafael., Razi, A., Parr, T., Kirchhoff, M. & Friston, K. (2017). Biological self-organisation and Markov blankets Biological self-organisation and Markov blankets (pp. 1-25) BioRxiv : https://www.biorxiv.org/content/early/2017/11/30/227181

Url


  • https://www.biorxiv.org/content/early/2017/11/30/227181

Number Of Pages


  • 24

Start Page


  • 1

End Page


  • 25

Place Of Publication


  • BioRxiv

Type Of Work


  • Other

Abstract


  • Biological self-organisation is a process of spontaneous pattern formation; namely the emergence of coherent and stable systemic configurations that distinguish themselves from their environment. This process can occur at various spatial scales: from the microscopic (giving rise to cells) to the macroscopic (the emergence of organisms). Self-organisation at each level is essential to account for the hierarchical organisation of living organisms (organelles within cells, within tissues, within organs, etc.). In this paper, we pursue the idea that Markov blankets – statistical boundaries separating states that are external to a system from its internal states – emerge at every possible level of the description of the (living) system. Through simulations, we show that the concept of a Markov blanket is fundamental in defining biological systems and underwrites the nature and form of interactions between successive levels of hierarchical structure. We demonstrate the validity of our argument using simulations, based on the normative principle of variational free energy minimisation. Specifically, we adopt a top-down approach to provide a proof of concept for the claim that the self-organisation of Markov blankets (and blankets of blankets) underwrites the self-evidencing, autopoietic behaviour of living systems.

Authors


  •   Palacios, Ensor (external author)
  •   Razi, Adeel (external author)
  •   Parr, Thomas (external author)
  •   Kirchhoff, Michael D.
  •   Friston, Karl (external author)

Publication Date


  • 2017

Citation


  • Palacios, E. Rafael., Razi, A., Parr, T., Kirchhoff, M. & Friston, K. (2017). Biological self-organisation and Markov blankets Biological self-organisation and Markov blankets (pp. 1-25) BioRxiv : https://www.biorxiv.org/content/early/2017/11/30/227181

Url


  • https://www.biorxiv.org/content/early/2017/11/30/227181

Number Of Pages


  • 24

Start Page


  • 1

End Page


  • 25

Place Of Publication


  • BioRxiv