MODELLING AND ANALYSIS OF SOME RANDOM PROCESS DATA FROM NEUROPHYSIOLOGY

Abstract

Models, graphs and networks are particularly useful for examining statistical dependencies amongst quantities via conditioning. In this article the nodal random variables are point processes. Basic to the study of statistical networks is some measure of the strength of (possibly directed) connections between the nodes. The coeficients of determination and of mutual information are considered in a study for inference concerning statistical graphical models. The focus of this article is simple networks. Both
second-order moment and threshold model-based analyses are presented. The article includes examples from neurophysiology.