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Practical Measures of Integrated Information for Time-Series Data
Open accessAbstract
A recent measure of 'integrated information', Φ(DM), quantifies the extent to which a system generates more information than the sum of its parts as it transitions between states, possibly reflecting levels of consciousness generated by neural systems. However, Φ(DM) is defined only for discrete Markov systems, which are unusual in biology; as a result, Φ(DM) can rarely be measured in practice. Here, we describe two new measures, Φ(E) and Φ(AR), that overcome these limitations and are easy to apply to time-series data. We use simulations to demonstrate the in-practice applicability of our measures, and to explore their properties. Our results provide new opportunities for examining information integration in real and model systems and carry implications for relations between integrated information, consciousness, and other neurocognitive processes. However, our findings pose challenges for theories that ascribe physical meaning to the measured quantities.
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Integrated information theory and its application for analysis of brain neuron activity
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A Phenomenological Glider? Enactivism and IIT in the Game of Life
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Metadata
- Authors
- Barrett, A. B., & Seth, A. K.
- Affiliations
- University of Sussex (GB)
- Corresponding author
- Barrett, Adam B.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-01-20
- Volume
- 7
- Issue
- 1
- Pages
- e1001052
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC3024259
- OpenAlex
- W2048013965
- Cited by
- 225
- References
- 61
- Citations by year
- 2026: 11 · 2025: 16 · 2024: 22 · 2023: 18 · 2022: 17 · 2021: 14 · 2020: 17 · 2019: 21 · 2018: 17 · 2017: 17 · 2016: 16 · 2015: 13 · 2014: 10 · 2013: 2 · 2012: 9
- FWCI
- 10.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Sussex Research Online (University of Sussex) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Engineering and Physical Sciences Research Council (EP/G007543/1)
- Topics
- Social Sciences › Arts and Humanities › Philosophy › Philosophy and Theoretical Science
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- integrated information, information integration, time series, Markov systems, consciousness, neural systems, information measures
- MeSH terms
- Information Services, Markov Chains, Models, Theoretical
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