Different Characteristics And Important Channels Between The Healthy Brain Network And The Epileptic Brain Network Based On EEG Data

In this thesis,the brain networks of the healthy and the epilepsy based on EEG are discussed by methods of nonlinear system and graph theory.This thesis mainly includes the following contents:firstly,two different brain networks are simulated with a chaotic Rulkov neuron model,and the dynamic characteristics of these two models are analyzed.Secondly,we study the important nodes of the neuron network.Thirdly,we give the corresponding phase diagrams of two identical Rulkov neuron networks under different parameter values.The specific contents are as follows:In chapter 1,we introduce the background,research status and some basic theories and methods of the nonlinear dynamical system used in this paper.In chapter 2,a neuron network in the brain is simulated by a model which contains N discrete two-dimension Rulkov neuron models connected by electri-cal coupling.In order to analyze the stability and synchronization of the network model,the derivation of the master stability equation of the network system is pre-sented by using the master stability function analysis.Furthermore,the conditions of stable synchronization of discrete Rulkov neuron networks are analyzed.In chapter 3,the discrete Rulkov neuron network models of N = 19 is con-sidered and the brain networks of healthy and the epileptic patients are simul-taneously simulated.The coupling between neurons in the brain is analyzed in two ways:linear coupling and nonlinear coupling.Through the master stability function analysis and numerical simulation,the maximum Lyapunov exponent di-agrams and the different characteristics of two brain neuron networks in different coupling system are obtained.Our study shows that when the coupling is linear,the two brain networks can not achieve stable complete synchronization,and when the coupling is nonlinear,there exists a = 2.95 such that the epileptic brain net-work can achieve stable synchronization for ε ∈[0.1678,0.1694],while the healthy brain network can not achieve stable synchronization.In chapter 4,according to the graph theory and the node index theory,node indexes of the brain neuron network are calculated,and analyzing which node in brain network play an important role for epileptic seizures by comparing the indexes of the epilepsy with those of the healthy,and the cause and focus of epilepsy are analyzed combined with clinical medicine.In chapter 5,we give the corresponding phase diagrams of two identical Rulkov neuron networks with electrical coupling under different parameter values.In chapter 6,we summarizes this paper.