Somatic multicellularity as a satisficing solution to the prediction-error minimization problem

Adaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive...

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Main Authors: Chris Fields, Michael Levin
Format: Article
Language:English
Published: Taylor & Francis Group 2019-01-01
Series:Communicative & Integrative Biology
Subjects:
Online Access:http://dx.doi.org/10.1080/19420889.2019.1643666
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spelling doaj-cb84e9ebebec462cb3683867a0da1d532021-02-02T05:31:18ZengTaylor & Francis GroupCommunicative & Integrative Biology1942-08892019-01-0112111913210.1080/19420889.2019.16436661643666Somatic multicellularity as a satisficing solution to the prediction-error minimization problemChris Fields0Michael Levin1Caunes Minervois, FranceAllen Discovery Center at Tufts UniversityAdaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive power. Here, we argue that this fundamental drive provides a novel perspective on the origin of multicellularity. One way for unicellular organisms to minimize surprise with respect to external inputs is to be surrounded by reproductively-disabled, i.e. somatic copies of themselves – highly predictable agents which in effect reduce uncertainty in their microenvironments. We show that the transition to multicellularity can be modeled as a phase transition driven by environmental threats. We present modeling results showing how multicellular bodies can arise if non-reproductive somatic cells protect their reproductive parents from environmental lethality. We discuss how a somatic body can be interpreted as a Markov blanket around one or more reproductive cells, and how the transition to somatic multicellularity can be represented as a transition from exposure of reproductive cells to a high-uncertainty environment to their protection from environmental uncertainty by this Markov blanket. This is, effectively, a transition by the Markov blanket from transparency to opacity for the variational free energy of the environment. We suggest that the ability to arrest the cell cycle of daughter cells and redirect their resource utilization from division to environmental threat amelioration is the key innovation of obligate multicellular eukaryotes, that the nervous system evolved to exercise this control over long distances, and that cancer is an escape by somatic cells from the control of reproductive cells. Our quantitative model illustrates the evolutionary dynamics of this system, provides a novel hypothesis for the origin of multicellular animal bodies, and suggests a fundamental link between the architectures of complex organisms and information processing in proto-cognitive cellular agents.http://dx.doi.org/10.1080/19420889.2019.1643666ancestral genetic toolkitcellular information processingfree-energy principlemarkov blanketpercolation theoryur-metazoan
collection DOAJ
language English
format Article
sources DOAJ
author Chris Fields
Michael Levin
spellingShingle Chris Fields
Michael Levin
Somatic multicellularity as a satisficing solution to the prediction-error minimization problem
Communicative & Integrative Biology
ancestral genetic toolkit
cellular information processing
free-energy principle
markov blanket
percolation theory
ur-metazoan
author_facet Chris Fields
Michael Levin
author_sort Chris Fields
title Somatic multicellularity as a satisficing solution to the prediction-error minimization problem
title_short Somatic multicellularity as a satisficing solution to the prediction-error minimization problem
title_full Somatic multicellularity as a satisficing solution to the prediction-error minimization problem
title_fullStr Somatic multicellularity as a satisficing solution to the prediction-error minimization problem
title_full_unstemmed Somatic multicellularity as a satisficing solution to the prediction-error minimization problem
title_sort somatic multicellularity as a satisficing solution to the prediction-error minimization problem
publisher Taylor & Francis Group
series Communicative & Integrative Biology
issn 1942-0889
publishDate 2019-01-01
description Adaptive success in the biosphere requires the dynamic ability to adjust physiological, transcriptional, and behavioral responses to environmental conditions. From chemical networks to organisms to whole communities, biological entities at all levels of organization seek to optimize their predictive power. Here, we argue that this fundamental drive provides a novel perspective on the origin of multicellularity. One way for unicellular organisms to minimize surprise with respect to external inputs is to be surrounded by reproductively-disabled, i.e. somatic copies of themselves – highly predictable agents which in effect reduce uncertainty in their microenvironments. We show that the transition to multicellularity can be modeled as a phase transition driven by environmental threats. We present modeling results showing how multicellular bodies can arise if non-reproductive somatic cells protect their reproductive parents from environmental lethality. We discuss how a somatic body can be interpreted as a Markov blanket around one or more reproductive cells, and how the transition to somatic multicellularity can be represented as a transition from exposure of reproductive cells to a high-uncertainty environment to their protection from environmental uncertainty by this Markov blanket. This is, effectively, a transition by the Markov blanket from transparency to opacity for the variational free energy of the environment. We suggest that the ability to arrest the cell cycle of daughter cells and redirect their resource utilization from division to environmental threat amelioration is the key innovation of obligate multicellular eukaryotes, that the nervous system evolved to exercise this control over long distances, and that cancer is an escape by somatic cells from the control of reproductive cells. Our quantitative model illustrates the evolutionary dynamics of this system, provides a novel hypothesis for the origin of multicellular animal bodies, and suggests a fundamental link between the architectures of complex organisms and information processing in proto-cognitive cellular agents.
topic ancestral genetic toolkit
cellular information processing
free-energy principle
markov blanket
percolation theory
ur-metazoan
url http://dx.doi.org/10.1080/19420889.2019.1643666
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