How causal analysis can reveal autonomy in models of biological systems
Open accessAbstract
Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system—whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause–effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause–effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast ( Schizosaccharomyces pombe ) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue ‘Reconceptualizing the origins of life’.
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IIT-based models of metabolic cycles and gene-regulatory networks suggest that adaptive capacities of biotic systems may require high-phi configurations.
“Notably, IIT-based models of metabolic cycles and gene-regulatory networks—core processes for homeostasis and autopoiesis—suggest that adaptive capacities of biotic systems may require high-phi configurations (Marshall et al., 2017; Abrego and Zaikin, 2019).”
From An Integrated World Modeling Theory (IWMT) of Consciousness (2020) · cites this paper as Marshall et al., 2017
The Boolean network model and Discussion report that IIT analysis found an integrated, self-regulating fission yeast cell-cycle network with self-maintained causal borders. They do not study metabolic cycles or establish that adaptive capacities generally require high-Φ configurations; the paper also notes that the cell-cycle function can be reproduced by a backbone network that is not integrated. Page numbers were not available in our copy. (LLM, conf=0.85)
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- Authors
- Marshall, W., Kim, H., Walker, S. I., Tononi, G., & Albantakis, L.
- Affiliations
- University of Wisconsin–Madison (US)
- Arizona State University (US)
- Corresponding author
- Albantakis, Larissa
- Venue
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Publisher
- The Royal Society
- Published
- 2017-11-13
- Volume
- 375
- Issue
- 2109
- Pages
- 20160358
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- PMC
- PMC5686412
- OpenAlex
- W2753865463
- Cited by
- 64
- References
- 32
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 5 · 2023: 7 · 2022: 6 · 2021: 9 · 2020: 11 · 2019: 9 · 2018: 7 · 2017: 1
- FWCI
- 40.29
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University) (cc-by)
- Funders
- Templeton World Charities Foundation (TWCF 0067/AB41)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Cellular Automata and Applications
- Keywords
- integrated information theory, causal architecture, biological autonomy, Boolean networks, Schizosaccharomyces pombe, cell cycle, origin of life
- MeSH terms
- Cell Cycle, Models, Biological, Schizosaccharomyces
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