https://doi.org/10.1140/epjst/e2014-02306-8
Regular Article
Brain network dynamics characterization in epileptic seizures
Joint directed graph and pairwise synchronization measures
1 Bioinformatics Interunits Graduate Program, University of São Paulo, São Paulo, Brazil
2 Hospital Israelita Albert Einstein, São Paulo, Brazil
3 Department of Neurology, School of Medicine, University of São Paulo, São Paulo, Brazil
4 Department of Neurosciences and Behavior, Ribeirão Preto School of Medicine, University of São Paulo, Ribeirão Preto, Brazil
5 Institute of Mathematic and Statistics, University of São Paulo, São Paulo, Brazil
6 Department of Telecommunications and Control Engineering, Escola Politécnica, University of São Paulo, São Paulo, Brazil
7 Department of Radiology and Oncology, School of Medicine, University of São Paulo, São Paulo, Brazil
a e-mail: abner@usp.br
Received: 27 May 2014
Revised: 17 October 2014
Published online: 10 December 2014
Here we propose and evaluate a new approach to analyse multichannel mesial temporal lobe epilepsy EEG data from eight patients through complex network and synchronization theories. The method employs a Granger causality test to infer the directed connectivity graphs and a wavelet transform based phase synchronization measure whose characteristics allow studying dynamical transitions during epileptic seizures. We present a new combined graph measure that quantifies the level of network hub formation, called network hub out-degree, which closely reflects the level of synchronization observed during the ictus.
© EDP Sciences, Springer-Verlag, 2014