Journal Article

Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate data

Rosas, Fernando E., Barrett, Adam B., Jensen, Henrik J., Mediano, Pedro A. M., Seth, Anil K., Bor, Daniel, Carhart-Harris, Robin L.

2020

Overview

The 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.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Animals / Behavior, Animal / Biology and life sciences / Birds / Case studies / Causality / Computational Biology / Computer and Information Sciences / Computer Simulation / Emergence (Systems theory) / Engineering and Technology / Haplorhini / Humans / Identification and classification / Information Theory / Medicine and Health Sciences / Models, Biological / Models, Statistical / Multivariate Analysis / Neurophysiology / Physical Sciences / Research and Analysis Methods / Social Sciences / Structural equation modeling / Substrates