Measuring integrated information: comparison of candidate measures in theory and simulation

Mediano, Pedro M, Seth, Anil and Barrett, Adam (2018) Measuring integrated information: comparison of candidate measures in theory and simulation. Entropy, 21 (1). pp. 1-30. ISSN 1099-4300

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Abstract

Integrated Information Theory (IIT) is a prominent theory of consciousness that has at its centre measures that quantify the extent to which a system generates more information than the sum of its parts. While several candidate measures of integrated information (‘Φ’) now exist, little is known about how they compare, especially in terms of their behaviour on non-trivial network models. In this article we provide clear and intuitive descriptions of six distinct candidate measures. We then explore the properties of each of these measures in simulation on networks consisting of eight interacting nodes, animated with Gaussian linear autoregressive dynamics. We find a striking diversity in the behaviour of these measures – no two measures show consistent agreement across all analyses. Further, only a subset of the measures appear to genuinely reflect some form of dynamical complexity, in the sense of simultaneous segregation and integration between system components. Our results help guide the operationalisation of IIT and advance the development of measures of integrated information that may have more general applicability.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
School of Mathematical and Physical Sciences > Physics and Astronomy
Research Centres and Groups: Centre for Computational Neuroscience and Robotics
Sackler Centre for Consciousness Science
Subjects: B Philosophy. Psychology. Religion > BF Psychology > BF0311 Consciousness. Cognition
Depositing User: Marianne Cole
Date Deposited: 19 Dec 2018 14:10
Last Modified: 01 Jul 2019 15:30
URI: http://sro.sussex.ac.uk/id/eprint/80904

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