Multidimensional Directed Information and Its Application

Abstract

SUMMARYBrain 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. © 2001 Scripta Technica, Electron Comm Jpn Pt 3, 85(4): 4555, 2002

Estimation of the number of EEG sources in the human brain using multidimensional directed information analysis

“…5 and 7, and the cross-correlation value according to Eq. This is because analysis based on cross-correlation ignores temporal relations, so that nonexistent sources become involved [15]. 6 and 8; the time shift is plotted on the horizontal axis in all cases.…”

“…The cross-correlation analysis results depend on the threshold setting to some extent but even in the most common case of 0.4, all time series are recognized as information sources, and the number of sources reaches 10 or more. This is because analysis based on cross-correlation ignores temporal relations, so that nonexistent sources become involved [15]. Normally, the brain waves of a person at rest, with eyes closed, are assumed to have up to a dozen sources.…”

“…8-13. The authors, too, have extended existing methods to propose multidimensional directed coherence analysis [14] and multidirectional directed information analysis [15], and have examined the application of these methods to brain wave analysis.…”

Fast multidimensional directed information analysis

“…We proposed a method for the causality analysis of multidimensional time series based on the novel concept of multidimensional directed information (MDI) analysis. The MDI analysis quantifies and visualizes causal relationships in a multidimensional time series as well as spatial-temporal correlations as 'information flows' in the time domain [14,15]. The physical relevance of 'information flow' is a Correspondence to: Osamu Sakata.…”

Short-time multidimensional directed coherence for EEG Analysis

“…In the case of the correlation function, the direction of information flow can be determined from the phase difference if the flow is one-way, but detection becomes difficult when there are two or more components flowing in two directions. In contrast, there are methods suited to causality analysis, such as directed-coherence analysis [1][2][3][4], innovation analysis [5], directed-information analysis [6,7], multidimensional directed-information analysis [8,9], Kaminski's method (DTF) [10,11], partial directed coherence [12,13], and…”