Advances and Applications in Statistics
Volume 42, Issue 1, Pages 65 - 82
(September 2014)
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PARTIAL DIRECTED COHERENCE APPLICATIONS ON EEG DATA
Kim Samejima M. Lopes
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Abstract: This article is a review on multivariate time series relationship and its applications in electroencephalogram (EEG) data. We discussed the coherence function, an analogous function to the linear correlation function. We also studied partial coherence (PC) and partial directed coherence(PDC)functions.ThePCfunctionmeasures therelationship between two components of a multivariate time series when isolating effects of another series. Generally, PDC can be interpretedasthedecompositionofpartialcoherenceinto multivariate autoregressive models, i.e., as a representation of Granger causality in the frequency domain. Finally, we applied those functions into EEG data from a subject in the resting state. Those functions are very interesting when we are interested not only on the correlation between time series, but also on the causality between them. |
Keywords and phrases: time series, cross spectrum, coherence, partial coherence, partial directed coherence, EEG data. |
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