Integrated information theory (IIT) is a theoretical framework for understanding consciousness developed by Dr. Giulio Tononi and collaborators at the Center 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 library for
calculating integrated information (denoted Φ) and its associated
quantities and structures. It is open-source and available on
GitHub, and can be installed on the
command line with the Python package manager via
pip install pyphi.
The figures in the IIT 3.0 paper are illustrated with PyPhi as an IPython notebook and in the online documentation. This section is meant to serve as a companion to the paper, and readers are encouraged to follow along and analyze the systems shown in the figures, hopefully becoming more familiar with both the theory and the software in the process.
Please consult the the project's README for more information.
There is a visual interface to this code available on this website via the “Calculate Φ” tab above.
Additionally, the source code itself is commented. Those familiar with Python are encouraged to read the code to better understand the details of the calculation.
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.