Statistical physics approach in epilepsy disease

Epilepsy is a central nervous system disorder in which brain activity becomes abnormal, causing seizures or periods of abnormal behavior, emotions, and sometimes loss of consciousness. Having a seizure does not mean that a person has epilepsy. At least two seizures without a known trigger (unprovoked seizures) occurring at least ۲۴ hours apart are usually required for a diagnosis of epilepsy. Epilepsy studies often rely on EEG signals to provide information about brain behavior during seizures. In this research, we used two network-based statistical analysis methods to classify the EEG data recorded by Bonn University of Bonn. The first method was based on correlation between two time series and the second method was based on quantile networks. In the next step, we examined the networks built in two ways, for healthy and diseased groups, according to several network topological criteria. Correlation-based networks are a complex network construction method using one-dimensional time series. Each channel is considered as a vertex of the complex network. If there is a relationship between two time series, that means there is an edge between the two vertices. The purpose of using this method is to compare the degree of connection between di↵erent brain areas.Recently, a mapping of a time series to a network has been proposed, based on the concept of transition probabilities. This series results in a”quantile graph”(QG). The purpose of using this method is to obtain the relationship of di↵erent areas of the frequency ranges of each of the signals. Based on di↵erent network criteria, i.e. clustering coefficient and betweenness centrality, the obtained results showed that the correlation method and the QG method are able to detect di↵erences in the dynamic properties of brain electrical activity.Comparing the correlation networks of patient and healthy people, it was concluded that the networks of patient people are denser and the quantile networks are denser in healthy people. This problem can be used as a diagnostic panel for EEG signal data to diagnose epilepsy.

کلیدواژه ها:

Epilepsy ، Electroencephalographic time series ، Complex network ، Network correlation ، QG-method