Integrated Information Theory

Integrated information theory (IIT) is a theoretical framework for understanding consciousness developed by Dr. Giulio Tononi and collaborators at the Wisconsin Institute for Sleep and Consciousness at the University of Wisconsin–Madison.



PyPhi is a Python software package for calculating integrated information and its associated structures. For more information, please see our paper describing the software:

Mayner WGP, Marshall W, Albantakis L, Findlay G, Marchman R, Tononi G. (2018)
PyPhi: A toolbox for integrated information theory.
PLOS Computational Biology 14(7): e1006343.

Please cite this paper if you use PyPhi in your research.

PyPhi is open-source and available on GitHub, and can be installed on the command line with the Python package manager via pip install pyphi.


For discussion about the software or integrated information theory in general, you can join the PyPhi users group.


Online documentation is available. There are examples that demonstrate how to create a network and measure its integrated information, and comprehensive documentation of the API.

For technical issues with PyPhi or feature requests, please use the GitHub issues page.

Colab Notebook

Please see our Colab Notebook, in which you can learn about IIT while using PyPhi interactively.