Literature DB >> 30048445

PyPhi: A toolbox for integrated information theory.

William G P Mayner1,2, William Marshall2, Larissa Albantakis2, Graham Findlay1,2, Robert Marchman2, Giulio Tononi2.   

Abstract

Integrated information theory provides a mathematical framework to fully characterize the cause-effect structure of a physical system. Here, we introduce PyPhi, a Python software package that implements this framework for causal analysis and unfolds the full cause-effect structure of discrete dynamical systems of binary elements. The software allows users to easily study these structures, serves as an up-to-date reference implementation of the formalisms of integrated information theory, and has been applied in research on complexity, emergence, and certain biological questions. We first provide an overview of the main algorithm and demonstrate PyPhi's functionality in the course of analyzing an example system, and then describe details of the algorithm's design and implementation. PyPhi can be installed with Python's package manager via the command 'pip install pyphi' on Linux and macOS systems equipped with Python 3.4 or higher. PyPhi is open-source and licensed under the GPLv3; the source code is hosted on GitHub at https://github.com/wmayner/pyphi. Comprehensive and continually-updated documentation is available at https://pyphi.readthedocs.io. The pyphi-users mailing list can be joined at https://groups.google.com/forum/#!forum/pyphi-users. A web-based graphical interface to the software is available at http://integratedinformationtheory.org/calculate.html.

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Year:  2018        PMID: 30048445      PMCID: PMC6080800          DOI: 10.1371/journal.pcbi.1006343

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  10 in total

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2.  Unified framework for information integration based on information geometry.

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Review 4.  Integrated information theory: from consciousness to its physical substrate.

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Journal:  Nat Rev Neurosci       Date:  2016-05-26       Impact factor: 34.870

5.  Integrated information in discrete dynamical systems: motivation and theoretical framework.

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Journal:  PLoS Comput Biol       Date:  2008-06-13       Impact factor: 4.475

6.  An information integration theory of consciousness.

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Journal:  BMC Neurosci       Date:  2004-11-02       Impact factor: 3.288

7.  From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0.

Authors:  Masafumi Oizumi; Larissa Albantakis; Giulio Tononi
Journal:  PLoS Comput Biol       Date:  2014-05-08       Impact factor: 4.475

8.  Evolution of integrated causal structures in animats exposed to environments of increasing complexity.

Authors:  Larissa Albantakis; Arend Hintze; Christof Koch; Christoph Adami; Giulio Tononi
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10.  Integrated Information and State Differentiation.

Authors:  William Marshall; Jaime Gomez-Ramirez; Giulio Tononi
Journal:  Front Psychol       Date:  2016-06-28
  10 in total
  12 in total

1.  What Caused What? A Quantitative Account of Actual Causation Using Dynamical Causal Networks.

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Review 3.  Growing evidence for separate neural mechanisms for attention and consciousness.

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4.  How cognitive and environmental constraints influence the reliability of simulated animats in groups.

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Journal:  PLoS One       Date:  2020-02-07       Impact factor: 3.240

Review 5.  Entropy and the Brain: An Overview.

Authors:  Soheil Keshmiri
Journal:  Entropy (Basel)       Date:  2020-08-21       Impact factor: 2.524

6.  Evaluating Approximations and Heuristic Measures of Integrated Information.

Authors:  André Sevenius Nilsen; Bjørn Erik Juel; William Marshall
Journal:  Entropy (Basel)       Date:  2019-05-24       Impact factor: 2.524

7.  Four-Types of IIT-Induced Group Integrity of Plecoglossus altivelis.

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Journal:  Entropy (Basel)       Date:  2020-06-30       Impact factor: 2.524

8.  The Emergence of Integrated Information, Complexity, and 'Consciousness' at Criticality.

Authors:  Nicholas J M Popiel; Sina Khajehabdollahi; Pubuditha M Abeyasinghe; Francesco Riganello; Emily S Nichols; Adrian M Owen; Andrea Soddu
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9.  Integrated information structure collapses with anesthetic loss of conscious arousal in Drosophila melanogaster.

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Journal:  PLoS Comput Biol       Date:  2021-02-26       Impact factor: 4.475

10.  Emergence of informative higher scales in biological systems: a computational toolkit for optimal prediction and control.

Authors:  Erik Hoel; Michael Levin
Journal:  Commun Integr Biol       Date:  2020-08-15
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