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Exploring effective connectivity between neuronal assemblies at different temporal and spatial scales is an important issue in human brain research from the perspective of pervasive computing. At the same time, network motifs play roles in network classification and analysis of structural network properties. This paper develops a method of analyzing the(More)
This paper develops a method to explore effective connectivity for time-series by using Granger causality and complex network. The Granger causality of multivariable time-series are analyzed based on VAR model, by which the weighed causality graph is built up to reveal a variety of causal relationship among components of time-series. Then the directed and(More)
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