Multidimensional directed information and its application

Brain waves are derived as multiple time-series signals from electrodes placed on various sites on the scalp. If the flow of information among these multiple sites can be visualized, it will be useful in obtaining a clue to the objective interpretation of brain activity, or in diagnosing the existence of failures of brain function. Directed information analysis has been proposed as a means of causality analysis in which the flow of information among the signals is investigated. The method notes an arbitrary two of a large number of time series, and examines the flow of information between these. When three or more signal series exist, they are in general related to each other. Consequently, even if the causality between two particular series is to be examined, the accurate flow of information cannot be determined unless the effect of another series is considered. Consequently, the authors have proposed multidimensional directed information analysis, which is an extension of directed information analysis. This paper tries to verify the effectiveness of multidimensional directed information analysis by simulation. Then, the method is applied to the brain waves of a healthy subject and a patient with a cerebral organic disorder, and it is verified that there is a difference, reflecting the presence of disease in the sense of information propagation in the cortex.