Gaussian Partial Information Decomposition: Quantifying Inter-areal Interactions in High-Dimensional Neural Data
Praveen Venkatesh,Gabriel Schamberg,Adrienne Fairhall,Shawn Olsen,Stefan Mihalas,Christof Koch · COSYNE 2022
A fundamental problem in neuroscience is to understand the different ways in which brain areas can interact to encode information. When two brain areas interact with a third, what fraction of the mutual information between the former and the latter can be attributed uniquely to each of the former? What fraction is redundant between them, and what fraction is synergistic? These “partial information” components quantify how different brain areas interact, which can help us understand the efficiency of various neural coding or communication schemes. Information-theoretic measures called partial i
Fri, Mar 18, 2022