Order Patterns Networks (orpan) – a method toestimate time-evolving functional connectivity frommultivariate time series

• Main Authors: Stefan eSchinkel, Gorka eZamora-López, Olaf eDimigen, Werner eSommer, Jürgen eKurths
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2012-11-01
• Series: Frontiers in Computational Neuroscience
• Subjects: EEG; ERP; semantic priming; time series analysis; Functional Networks; network reconstruction
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fncom.2012.00091/full
• ISSN: 1662-5188

Complex networks provide an excellent framework for studying the functionof the human brain activity. Yet estimating functional networks from mea-sured signals is not trivial, especially if the data is non-stationary and noisyas it is often the case with physiological recordings. In this article we proposea method that uses the local rank structure of the data to define functionallinks in terms of identical rank structures. The method yields temporal se-quences of networks which permits to trace the evolution of the functionalconnectivity during the time course of the observation. We demonstrate thepotentials of this approach with model data as well as with experimentaldata from an electrophysiological study on language processing.