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由计算模型产生多通道神经信号,可帮助理解引起脑电信号节律的机制,研究大脑的功能联接以及测试神经信息处理的方法和假设.本文将双动力学集总参数神经群模型扩展为多动力学多通道耦合的模型,用于研究大脑不同区域的耦合动力学行为.通过模型仿真发现信号的频谱可以从δ波(1-4Hz)到γ波(30-70Hz)变化,其动力学特性更加复杂;模型实验还揭示了神经网络耦合和神经群节律之间的关系,随耦合强度的增强,新模型仿真信号会出现双谱峰和单谱峰的现象;通过模拟大鼠癫痫,也证实神经群之间的耦合可以导致癫痫大范围爆发.
The multi-channel neural signal generated by the computational model can help to understand the mechanisms that cause the rhythm of EEG signals, study the functional connection of the brain, and test the methods and assumptions of the neural information processing.In this paper, the dual-kinematic lumped parameter neural model is extended to multi- A multi-channel coupled model was developed to study the coupling dynamics in different regions of the brain. The simulation results show that the spectrum of the signal can vary from δ-wave (1-4Hz) to γ-wave (30-70Hz) The model experiment also reveals the relationship between the neural network coupling and the rhythm of the neural group. With the enhancement of the coupling strength, the phenomenon of bispectrum and singlet peak appears in the new model simulation signal. By simulating the rat epilepsy, it is also confirmed that the nerve The coupling between the groups can lead to the widespread outbreak of epilepsy.