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Quantifying causal emergence shows that macro can beat micro
Open accessAbstract
Significance: Properly characterizing emergence requires a causal approach. Here, we construct causal models of simple systems at micro and macro spatiotemporal scales and measure their causal effectiveness using a general measure of causation [effective information ( EI )]. EI is dependent on the size of the system’s state space and reflects key properties of causation (selectivity, determinism, and degeneracy). Although in the example systems the macro mechanisms are completely specified by their underlying micro mechanisms, EI can nevertheless peak at a macro spatiotemporal scale. This approach leads to a straightforward way of quantifying causal emergence as the supersedence of a macro causal model over a micro one.
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Metadata
- Authors
- Hoel, E. P., Albantakis, L., & Tononi, G.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Tononi, Giulio
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-11-18
- Volume
- 110
- Issue
- 49
- Pages
- 19790-19795
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3856819
- OpenAlex
- W2160448328
- Cited by
- 378
- References
- 5
- Citations by year
- 2026: 76 · 2025: 53 · 2024: 46 · 2023: 37 · 2022: 25 · 2021: 26 · 2020: 27 · 2019: 19 · 2018: 18 · 2017: 18 · 2016: 13 · 2015: 11 · 2014: 8
- FWCI
- 6.26
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Paul G. Allen Family Foundation
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Social Sciences › Arts and Humanities › Philosophy › Philosophy and Theoretical Science
- Keywords
- causal emergence, effective information, supervenience, micro and macro levels, coarse-graining, state space, causal architecture, complex systems, brain, determinism, degeneracy
- MeSH terms
- Computer Simulation, Information Theory, Models, Theoretical, Systems Biology
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