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Practical measures of integrated information for time-series data

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posted on 2023-06-09, 00:40 authored by Adam BarrettAdam Barrett, Anil SethAnil Seth
A recent measure of ‘integrated information’, FDM, 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, FDM is defined only for discrete Markov systems, which are unusual in biology; as a result, FDM can rarely be measured in practice. Here, we describe two new measures, FE and FAR, 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.

Funding

Towards a next-generation computational neuroscience; G0305; EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCIL; EP/G007543/1

History

Publication status

  • Published

File Version

  • Published version

Journal

PLoS Computational Biology

ISSN

1553-7358

Publisher

Public Library of Science

Issue

1

Volume

7

Department affiliated with

  • Informatics Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2016-03-30

First Open Access (FOA) Date

2016-03-30

First Compliant Deposit (FCD) Date

2016-03-29

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