Different characteristics and important channels between the healthy brain network and the epileptic brain network based on EEG data

In this paper, firstly, based on the clinic EEG data taken from 19 channels (electrodes, nodes) on human scalp, assuming that each electrode can be represented by a two-dimensional Rulkov chaotic neuron model, and the connectivity between any two electrodes may be the non-directional coupling, the healthy brain network and the epileptic brain network are established. Secondly, different dynamical characteristics between the two networks are investigated by the master stability function analysis (MSF). The research shows that the two networks are unlikely to achieve stable synchronization when the coupling is linear and α ≥ 2.8. When the coupling is nonlinear, there exist some α such that the epileptic brain network can achieve stable synchronization for ε ∈ [0.1678, 0.1694], while the healthy brain network is unlikely to achieve stable synchronization. Finally, based on graph theory and index of node importance, several kinds of evaluation indexes of node are calculated, such as degree, average path length and clustering coefficient. This investigation shows that the average degree and the average clustering coefficient of the epileptic brain network are larger than those of the healthy network. However, the average path length of the epileptic brain network is smaller than that of the healthy network. For other indexes, compared with the corresponding indexes of the healthy brain network, subgraph centricity, eigenvector, closeness and cumulated nomination of the epileptic brain network are increased or decreased, simultaneously. Channels Fp1, T5, Pz and Fp2 can be regarded as important focal zones for the occurrence of epilepsy.