MEG Reading Group
Gaussian Copula Mutual Information
I will present a recently developed statistical method: Gaussian Copula Mutual Information (GCMI). This provides a general, computationally efficient, flexible, and robust multivariate statistical framework, with effect sizes on a common meaningful scale, that allows for unified treatment of discrete, continuous, and multi-dimensional variables, and enables a range of analyses that go beyond traditional pairwise measures of dependence. I will then cover recent methods for quantifying synergistic and redundant interactions between different signals or stimuli.