Nonlinear Analysis of Electroencephalogram Based on Synchronization Likelihood

Due to the non-stationary characteristics of scalp electroencephalography (EEG), traditional analysis methods, such as coherent method, etc., can't well detect statistical dependencies between time series recorded. synchronization likelihood (SL) based on generalized synchronization has been introduced to overcome some limitations of coherent estimations. And it is applied to analyze real EEG signals. Simulation results of Henon mapping system and actual EEG data demonstrate that the SL method is suitable for measuring the relationship between non-stationary signals. The changes of brain synchronization of healthy subjects are studied from eye closed to eye open during rest. Results show that the synchronization of alpha rhythm is significantly reduced in almost all electrodes, and the brain activity has a certain inhibition. All the results show that the method is of great significance in the study of EEG. It provides certain reference for future EEG research.