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.
- Integrated information theory: from consciousness to its physical substrate
Nature Reviews Neuroscience (2016)
- From the phenomenology to the mechanisms of consciousness: integrated information theory 3.0
PLoS Computational Biology (2014)
- Integrated information theory
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. https://doi.org/10.1371/journal.pcbi.1006343
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.
For technical issues with PyPhi or feature requests, please use the GitHub issues page.
There is a visual interface to this code available on this website via the “Calculate Φ” tab above.