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Analysis of correlation dimension of EEG data in epilepsy in children


N.Yu. Semenova, V.S. Zakharov

The electroencephalogram (EEG) indicates current of the nervous processes in a brain. EEG is of great importance for analysis of mechanism of brain activity in the norm and a pathology. Special importance EEG has at epilepsy diagnostics. The purpose of our work is to apply a research technique of nonlinear dynamic systems to detection neurophysiologic patterns according to EEG data for healthy children and children with epilepsy. On EEG data received at examination healthy children and children with epilepsy, we recovered attractors in a two-dimensional phase space. Results of our analysis show, that for the healthy children in all channels EEG attractors are similar to stochastic system attractors. For the sick children during absence seizures the attractors recovered on tracings of the most of channels, specially frontal and temporal zones, is similar to characteristic of deterministic chaotic system. In cases of registration of the expressed local epileptiform activity on EEG the same regularities for one or two zones of a brain have been discovered. We calculated correlation dimension Dc and embedding dimension m for 16-channel EEG data from 10 healthy children and 12 patients with epilepsy. The signals were analysed before, during and after the absence seizures. In the absence seizures we could distinguish dynamical regions on the cerebral cortex, one that seemed to exhibit deterministic chaos whereas the other seemed to exhibit noise. The chaotic dynamics that one seems to observe is determined by a small number of variables (m = 5 ÷ 8) and has low complexity (Dc = 3.5  4.3). Before and after the seizures no chaos was found. In the EEG of healthy children no chaotic region was found. The application of non-linear signal analysis revealed the existence of differences in EEG dynamics of healthy children and patients with epilepsy. The electroencephalogram is a development of the most complicated bioelectrochemical processes descending in a brain. Based on the approaches explained in our job, it is possible to give the following interpreting of the received results. For healthy children (and out of an attack) units of the complex system which generate EEG signal, work largely independently, "separately", that reveal to a great extent the stochasticity which is found at their probe. The epilepsy reveals as some kind of synchronisation of separate units which one in the norm are more independent. During an absence seizure there is still a large synchronisation, determinisation of systems, occurrence of a signal which is closed to the periodic one. In period after absence seizures reverse process of a desynchronization, randomisation of system occurs. This approach may contribute to the understanding of brain activity and may be useful in clinical diagnosis.

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