Citing PyPhi

If you use PyPhi in your research, please cite the software paper and the papers that describe the theory.

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

@article{mayner2018pyphi,
  title={PyPhi: A toolbox for integrated information theory},
  author={Mayner, William GP and Marshall, William and Albantakis, Larissa and Findlay, Graham and Marchman, Robert and Tononi, Giulio},
  journal={PLoS Computational Biology},
  volume={14},
  number={7},
  pages={e1006343},
  year={2018},
  publisher={Public Library of Science},
  doi={10.1371/journal.pcbi.1006343},
  url={https://doi.org/10.1371/journal.pcbi.1006343}
}

IIT 4.0

IIT 4.0 is described in two papers; cite both.

Albantakis L, Barbosa L, Findlay G, Grasso M, Haun AM, Marshall W, Mayner WGP, Zaeemzadeh A, Boly M, Juel BE, Sasai S, Fujii K, David I, Hendren J, Lang JP, Tononi G. (2023). Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms. PLOS Computational Biology 19(10): e1011465. https://doi.org/10.1371/journal.pcbi.1011465

@article{albantakis2023iit4,
  title={Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms},
  author={Albantakis, Larissa and Barbosa, Leonardo and Findlay, Graham and Grasso, Matteo and Haun, Andrew M and Marshall, William and Mayner, William GP and Zaeemzadeh, Alireza and Boly, Melanie and Juel, Bj{\o}rn E and Sasai, Shuntaro and Fujii, Keiko and David, Isaac and Hendren, Jeremiah and Lang, Jonathan P and Tononi, Giulio},
  journal={PLoS Computational Biology},
  volume={19},
  number={10},
  pages={e1011465},
  year={2023},
  publisher={Public Library of Science},
  doi={10.1371/journal.pcbi.1011465},
  url={https://doi.org/10.1371/journal.pcbi.1011465}
}

Mayner WGP, Marshall W, Tononi G. (2026). Intrinsic cause–effect power: the tradeoff between differentiation and specification. Entropy 28(4): 410. https://doi.org/10.3390/e28040410

@article{mayner2026intrinsic,
  title={Intrinsic cause--effect power: the tradeoff between differentiation and specification},
  author={Mayner, William GP and Marshall, William and Tononi, Giulio},
  journal={Entropy},
  volume={28},
  number={4},
  pages={410},
  year={2026},
  publisher={MDPI},
  doi={10.3390/e28040410},
  url={https://doi.org/10.3390/e28040410}
}

Earlier versions

For results computed under IIT 3.0, cite:

Oizumi M, Albantakis L, Tononi G. (2014). From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0. PLOS Computational Biology 10(5): e1003588. https://doi.org/10.1371/journal.pcbi.1003588

@article{oizumi2014iit3,
  title={From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0},
  author={Oizumi, Masafumi and Albantakis, Larissa and Tononi, Giulio},
  journal={PLoS Computational Biology},
  volume={10},
  number={5},
  pages={e1003588},
  year={2014},
  publisher={Public Library of Science},
  doi={10.1371/journal.pcbi.1003588},
  url={https://doi.org/10.1371/journal.pcbi.1003588}
}