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Evolving networks in the human epileptic brain

  • Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.

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Metadaten
Author:Klaus Lehnertz, Gerrit Ansmann, Stephan BialonskiORCiD, Henning Dickten, Christian Geier, Stephan Porz
DOI:https://doi.org/10.1016/j.physd.2013.06.009
ISSN:0167-2789
Parent Title (English):Physica D: Nonlinear Phenomena
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Article
Language:English
Year of Completion:2014
Date of the Publication (Server):2018/10/09
Volume:267
First Page:7
Last Page:15
Link:https://doi.org/10.1016/j.physd.2013.06.009
Zugriffsart:bezahl
Institutes:FH Aachen / Fachbereich Medizintechnik und Technomathematik
collections:Verlag / Elsevier