Assessment of linear and non-linear EEG synchronization measures for evaluating mild epileptic signal patterns

Epilepsy is one of the most common brain disorders and may result in brain dysfunction and cognitive disturbances. Epileptic seizures usually begin in childhood without being accommodated by brain damage and many drugs produce no brain dysfunction. In this study cognitive function in mild epilepsy cases is evaluated where children with seizures are compared to controls i.e., children with epileptic seizures, without brain damage and under drug control. Two different cognitive tasks were designed and performed by both the epileptic and healthy children: i) a relatively difficult math task and ii) Fractal observation. Under this prism, we investigate seven measures of quantifying synchronous oscillatory activity based on different underlying assumptions. Namely, the most widely used coherence, a coding-based measure known as MDL (Minimum Description Length) and the Geweke alternative, a robust phase coupling measure known as PLV (Phase Locking Value), a cortical synchrony measure defined from the embedding dimension in state-space called S-estimator, a reliable way of assessing generalized synchronization also in state-space and an unbiased alternative called Synchronization likelihood. Assessment was performed in three stages; initially the methods were validated on coupled nonlinear oscillators, secondly surrogate data testing was performed to assess the possible nonlinear nature of the acquired EEGs and finally synchronization on the actual data was measured. The results on the actual data suggest higher frequency band gamma2 was mostly apparent in occipitalparietal lobes during fractal tests. Manuscript received June 30, 2006. This work was supported in part by the EC IST project BIOPATTERN, Contract No: 508803. The work of C.D. Giurcăneanu and Y. Yang was supported by Academy of Finland, project No. 213462 (Finnish Centre of Excellence Program 2006-2011). V. Sakkalis is with the Department of Electronic and Computer Engineering, Technical University of Crete, Chania 73100 and the Institute of Computer Science, Foundation for Research and Technology, Heraklion 71110, Greece (+30-281-0391448; fax: +30-281-0391609; e-mail: [email protected]). C.D. Giurcăneanu and Y. Yang are with the Institute of Signal Processing, Tampere University of Technology, Tampere FIN-33101, Finland (e-mail: [email protected], yinghua yang @tut.fi). P. Xanthopoulos and M. Zervakis are with the Department of Electronic and Computer Engineering, Technical University of Crete, Chania 73100, Greece (e-mail: [email protected], [email protected]). V. Tsiaras is with the Institute of Computer Science, Foundation for Research and Technology, Heraklion, Greece and the Department of Computer Science, University of Crete, Heraklion 71409, Greece (email:[email protected]). S. Micheloyannis is with the Clinical Neurophysiology Laboratory (L. Widen), Faculty of Medicine, University of Crete, Heraklion 71409, Greece (e-mail: [email protected]).