In this section
@article{Rosas:2019:10.1103/physreve.100.032305,
author = {Rosas, FE and Mediano, PAM and Gastpar, M and Jensen, HJ},
doi = {10.1103/physreve.100.032305},
journal = {Physical Review E},
title = {Quantifying high-order interdependencies via multivariate extensions of the mutual information},
url = {http://dx.doi.org/10.1103/physreve.100.032305},
volume = {100},
year = {2019}
}
TY - JOUR
AB - This paper introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information, and introduces the O-information as a metric that is capable of characterizing synergy- and redundancy-dominated systems. The O-information is a symmetric quantity, and can assess intrinsic properties of a system without dividing its parts into “predictors” and “targets.” We develop key analytical properties of the O-information, and study how it relates to other metrics of high-order interactions from the statistical mechanics and neuroscience literature. Finally, as a proof of concept, we present an exploration on the relevance of statistical synergy in Baroque music scores.
AU - Rosas,FE
AU - Mediano,PAM
AU - Gastpar,M
AU - Jensen,HJ
DO - 10.1103/physreve.100.032305
PY - 2019///
SN - 2470-0045
TI - Quantifying high-order interdependencies via multivariate extensions of the mutual information
T2 - Physical Review E
UR - http://dx.doi.org/10.1103/physreve.100.032305
UR - http://hdl.handle.net/10044/1/73546
VL - 100
ER -