Testing for directed influences among neural signals using partial directed coherence

Björn Schelter, Matthias Winterhalder, Michael Eichler, Martin Peifer, Bernhard Hellwig, Brigitte Guschlbauer, Carl Hermann Lucking, Rainer Dahlhaus, Jens Timmer

Research output: Contribution to journalArticlepeer-review

235 Citations (Scopus)


One major challenge in neuroscience is the identification of interrelations between signals reflecting neural activity. When applying multivariate time series analysis techniques to neural signals, detection of directed relationships, which can be described in terms of Granger-causality, is of particular interest. Partial directed coherence has been introduced for a frequency domain analysis of linear Granger-causality based on modeling the underlying dynamics by vector autoregressive processes. We discuss the statistical properties of estimates for partial directed coherence and propose a significance level for testing for nonzero partial directed coherence at a given frequency. The performance of this test is illustrated by means of linear and non-linear model systems and in an application to electroencephalography and electromyography data recorded from a patient suffering from essential tremor. (c) 2005 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)210-219
Number of pages10
JournalJournal of Neuroscience Methods
Issue number1-2
Early online date2 Nov 2005
Publication statusPublished - 15 Apr 2006


  • partial directed coherence
  • Granger-causality
  • multivariate time series
  • graphical models


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