Multi-channel neural mass modelling and analyzing

Multi-channel neural signals generated by a computational model can help understand the mechanism of EEG rhythms, analyze brain functional connectivity and evaluate neural signal processing methods. In this study, a two-kinetics lumped-parameter neural mass model is extended to a multi-kinetics and multi-channel coupled model. This new model can effectively simulate the coupled dynamics activities between different areas in the brain. The simulation results show that the proposed model can generate neural signals with various frequency bands, from delta wave (1-4 Hz) to gamma wave (30-70 Hz), and the dynamics of the simulated neural signals is more complicated. The simulation analysis can also reveal the relationship between the coupled neural networks and the rhythm of neural populations, and the simulated neural signals can present the bi-modal and uni-modal phenomenon in the frequency domain when the coupling strength of models increases. Finally, analysis of an epileptic EEG signal from a rat demonstrates that the coupling among the neural populations can induce a large-scale seizure.