Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements
1
Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison, Madison, WI 53719, USA
2
Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI 53719, USA
*
Author to whom correspondence should be addressed.
†
Current address: Kettering University, 1700 University Ave., Flint, MI 48504, USA.
‡
Current address: New York University, Department of Biology, 100 Washington Square E #1009, New York, NY 10003, USA.
§
These authors contributed equally to this work.
Entropy 2021, 23(1), 6; https://doi.org/10.3390/e23010006
Received: 21 November 2020
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Revised: 15 December 2020
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Accepted: 17 December 2020
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Published: 22 December 2020
(This article belongs to the Special Issue Integrated Information Theory and Consciousness)
Integrated information theory (IIT) provides a mathematical framework to characterize the cause-effect structure of a physical system and its amount of integrated information (
Keywords:
causation; regulatory networks; binarization; coarse graining
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MDPI and ACS Style
Gomez, J.D.; Mayner, W.G.P.; Beheler-Amass, M.; Tononi, G.; Albantakis, L. Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements. Entropy 2021, 23, 6. https://doi.org/10.3390/e23010006
AMA Style
Gomez JD, Mayner WGP, Beheler-Amass M, Tononi G, Albantakis L. Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements. Entropy. 2021; 23(1):6. https://doi.org/10.3390/e23010006
Chicago/Turabian StyleGomez, Juan D., William G.P. Mayner, Maggie Beheler-Amass, Giulio Tononi, and Larissa Albantakis. 2021. "Computing Integrated Information (Φ) in Discrete Dynamical Systems with Multi-Valued Elements" Entropy 23, no. 1: 6. https://doi.org/10.3390/e23010006
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