Practical PHI Toolbox

<p>This MATLAB toolbox provides codes for computing practical measures of integrated information proposed in Oizumi et al., 2016, PLoS Comp Biol and Oizumi et al., 2016, PNAS and codes for efficiently searching the Minimum Information Partition (MIP) proposed in Hidaka & Oizumi, 2018, PLoS ONE and Kitazono et al., 2018, Entropy (Queyranne’s algorithm). Please see Readme.docx for more details. </p><p>The codes for Queyranne’s algorithm were written by Shohei Hidaka at JAIST (Japan Advanced Institute of Science and Technology).<br></p><p><br></p> <p> </p> <p>References</p> <p>[1] Oizumi, M., Amari, S, Yanagawa, T., Fujii, N., & Tsuchiya, N. (2016). Measuring integrated information from the decoding perspective. PLoS Comput Biol, 12(1), e1004654. </p> <p> </p> <p>[2] Oizumi, M., Tsuchiya, N., & Amari, S. (2016). Unified framework for information integration based on information geometry. Proceedings of the National Academy of Sciences, 113(51), 14817-14822. </p> <p> </p> <p>[3] Hidaka, S., & Oizumi, M. (2018). Fast and exact search for the partition with minimal information loss. PLoS one, 13(9), e0201126.</p> <p> </p> <p>[4] Kitazono, J., Kanai, R., Oizumi, M. (2018). Efficient algorithms for searching the minimum information partition in integrated information theory. Entropy, 20, 173.</p>