Literature DB >> 32212028

The information theory of individuality.

David Krakauer1, Nils Bertschinger2, Eckehard Olbrich3, Jessica C Flack4, Nihat Ay4,3.   

Abstract

Despite the near universal assumption of individuality in biology, there is little agreement about what individuals are and few rigorous quantitative methods for their identification. Here, we propose that individuals are aggregates that preserve a measure of temporal integrity, i.e., "propagate" information from their past into their futures. We formalize this idea using information theory and graphical models. This mathematical formulation yields three principled and distinct forms of individuality-an organismal, a colonial, and a driven form-each of which varies in the degree of environmental dependence and inherited information. This approach can be thought of as a Gestalt approach to evolution where selection makes figure-ground (agent-environment) distinctions using suitable information-theoretic lenses. A benefit of the approach is that it expands the scope of allowable individuals to include adaptive aggregations in systems that are multi-scale, highly distributed, and do not necessarily have physical boundaries such as cell walls or clonal somatic tissue. Such individuals might be visible to selection but hard to detect by observers without suitable measurement principles. The information theory of individuality allows for the identification of individuals at all levels of organization from molecular to cultural and provides a basis for testing assumptions about the natural scales of a system and argues for the importance of uncertainty reduction through coarse-graining in adaptive systems.

Entities:  

Keywords:  Adaptation; Control; Evolution; Gestalt; Information decomposition; Mutual information; Shannon information; Shared information; Synergy

Mesh:

Year:  2020        PMID: 32212028      PMCID: PMC7244620          DOI: 10.1007/s12064-020-00313-7

Source DB:  PubMed          Journal:  Theory Biosci        ISSN: 1431-7613            Impact factor:   1.919


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