Date: July 13, 2009
Creator: Gintautas, Vadas; Bettencourt, Luis & Ham, Michael I.
Description: This paper accompanies an oral presentation on the identification of functional information subgraphs in cultured neural networks. Abstract: We present a general information theoretic approach for identifying functional subgraphs in complex neuronal networks where the spiking dynamics of a subset of nodes (neurons) are observable. We show that the uncertainty in the state of each node can be written as a sum of information quantities involving a growing number of variables at other nodes. We demonstrate that each term in this sum is generated by successively conditioning mutual information on new measured variables, in a way analogous to a discrete differential calculus.
Contributing Partner: UNT College of Arts and Sciences