Epileptic Left-right Brain Network Analysis Based on Kendall's Improved Synchronization Algorithm

Complex networks can be regarded as an abstraction of the description of a complex system. This paper presents an improved nonlinear synchronization algorithm IRC (inverse rank correlation) based on Kendall rank correlation. The IRC coupling coefficient is asymmetric. The brain function network has directionality by constructing with the IRC coupling coefficient matrices, which is helpful to study the nonlinear dynamic behavior of the brain network. The IRC algorithm was used to construct the left and right brain functional networks based on multi-channel EEG data, and the average degree index of the regional brain function network was analyzed to study the similarities and differences of regional brain networks between epilepsy patients and normal people. The results show that the improved algorithm can significantly distinguish between epilepsy and normal left brain region functional networks, in which the complexity of the epilepsy and the normal left brain are different. The experimental data show that the analysis of IRC network will help the clinical diagnosis and analysis of epilepsy, further deepen the study of the neurological dynamics of the brain, and provide an effective tool for clinical diagnosis.