Identification of focal epileptic regions from electroencephalographic data: Feigenbaum graphs

G. Guarneros, C. Pérez, A. Montiel, J. F. Rojas


In the study of problems related to epilepsy analyzing electroencephalograms data is of much importance to help, one hand, to its diagnosis, and, another hand in the possibility of diminishing errors in surgery. We do this analysis making the Feigenbaum graphs for real electroencephalographic signals data sets and calculating characteristic networks (graph) quantities, such as average clustering, degree distribution, and average shortest path length. 
We manage to characterize two different data sets from each other, from data sets corresponding to focal and non-focal neuronal activity both time out of an epileptic seizure. This method enables us to identify sets of data from epileptic focal zones and suggest our approach could be used to aid physicians with diagnosing epilepsy from electroencephalographic data and/or in an exact establishment of the epileptic focal region for surgery.


EEG, Epilepsy, Statistical Physics methods, Feigenbaum graphs, visibility graph

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