Evaluation of Some Physiological Statements about Seizure, Using Processing of Epileptic EEG Signals

Seizure genesis is usually attributed to imbalance of the excitation and inhibition activities of neurons. It is claimed that slow inhibition mechanism is responsible for controlling the variations of the excitation mechanism, and any deficiency in this function will lead to disturbance of their natural balance. Fast inhibition mechanism is also known to collaborate with slow inhibitory processes. Any proof about the excitation and inhibition mechanisms refers to the ex-vivo or in-vitro experiments, i.e. from the microscopic point of view. Up to now, there is not a straight road into evaluating these hypotheses from the macroscopic view. In this paper we try to interpret the excitation-inhibition sequences extracted from some depth-EEG signals through an identification-based procedure. The aim is to check out whether the statements gained from microscopic observations are re-established in population of neurons in the case of MTLE or not. Using Neyman-Pearson hypothesis test technique we try to answer these questions. We observe that even in population of neurons slow inhibition is responsible for compensating excitatory processes to balance inhibitory /excitatory ratio, such that when it is impaired causes seizures to arise; also the average fast inhibitory process of population of neurons follows its slow inhibition dynamics. Also, we check the differentiation of the excitation-inhibition ratio between normal and ictal states, as well as between normal and pre-ictal states. Ictal activity is properly a state of abnormal high excitation-inhibition ratio but before beginning of seizures there are not unique patterns.

Keywords:

Seizure , excitation , inhibition , Neyman- Pearson decision algorithm