Time-variant estimation of directed influences during Parkinsonian tremor

Linda Sommerlade, Kathrin Henschel, Johannes Wohlmuth, Michael Jachan, Florian Amtage, Bernhard Hellwig, Carl Hermann Luecking, Jens Timmer, Bjoern Schelter

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


The inference of interaction structures in multidimensional time series is a major challenge not only in neuroscience but in many fields of research. To gather information about the connectivity in a network from measured data, several parametric as well as non-parametric approaches have been proposed and widely examined. Today a lot of interest is focused on the evolution of the network connectivity in time which might contain information about ongoing tasks in the brain or possible dynamic dysfunctions. Therefore an extension of the current approaches towards time-resolved analysis techniques is desired. We present a parametric approach for time variant analysis, test its performance for simulated data, and apply it to real-world data. (C) 2009 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)348-352
Number of pages5
JournalJournal of Physiology - Paris
Issue number6
Publication statusPublished - Nov 2009


  • multivariate time series
  • partial directed coherence
  • time-variant estimation


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