journal.pcbi.1008289.pdf (4.21 MB)
Reconciling emergences: an information-theoretic approach to identify causal emergence in multivariate data
Version 2 2023-06-12, 09:27
Version 1 2023-06-09, 21:29
journal contribution
posted on 2023-06-12, 09:27 authored by Fernando E Rosas, Pedro A M Mediano, Henrik J Jensen, Anil SethAnil Seth, Adam BarrettAdam Barrett, Robin L Carhart-Harris, Daniel BorThe broad concept of emergence is instrumental in various of the most challenging open scientific questions—yet, few quantitative theories of what constitutes emergent phenomena have been proposed. This article introduces a formal theory of causal emergence in multivariate systems, which studies the relationship between the dynamics of parts of a system and macroscopic features of interest. Our theory provides a quantitative definition of downward causation, and introduces a complementary modality of emergent behaviour—which we refer to as causal decoupling. Moreover, the theory allows practical criteria that can be efficiently calculated in large systems, making our framework applicable in a range of scenarios of practical interest. We illustrate our findings in a number of case studies, including Conway’s Game of Life, Reynolds’ flocking model, and neural activity as measured by electrocorticography.
Funding
The Sackler Centre for Consciousness Science 2019-2021 Leading-edge consciousness science and its application to psychological and neurological health; G2608; SACKLER-DR MORTIMER AND THERESA SACKLER FOUNDATION
History
Publication status
- Published
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- Published version
Journal
PLoS Computational BiologyISSN
1553-734XPublisher
Public Library of ScienceExternal DOI
Issue
12Volume
16Page range
1-23Article number
a1008289Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2020-09-03First Open Access (FOA) Date
2020-09-03First Compliant Deposit (FCD) Date
2020-09-02Usage metrics
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