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Analysis of structural patterns in the brain with the complex network approach

机译:复杂网络方法对大脑结构模式分析

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In this paper we study mechanisms of the phase synchronization in a model network of Van der Pol oscillators and in the neural network of the brain by consideration of macroscopic parameters of these networks. As the macroscopic characteristics of the model network we consider a summary signal produced by oscillators. Similar to the model simulations, we study EEG signals reflecting the macroscopic dynamics of neural network. We show that the appearance of the phase synchronization leads to an increased peak in the wavelet spectrum related to the dynamics of synchronized oscillators. The observed correlation between the phase relations of individual elements and the macroscopic characteristics of the whole network provides a way to detect phase synchronization in the neural networks in the cases of normal and pathological activity.
机译:本文通过考虑这些网络的宏观参数,研究van der Pol振荡器模型网络中的相位同步的机制,以及通过这些网络的宏观参数在大脑的神经网络中。作为模型网络的宏观特征,我们考虑振荡器产生的摘要信号。类似于模型仿真,我们研究反映神经网络宏观动态的EEG信号。我们表明,相位同步的外观导致与同步振荡器的动态相关的小波谱中的增加的峰值。观察到各个元素的相位关系与整个网络的宏观特征之间的相关性提供了在正常和病理活动的情况下检测神经网络中的相位同步的方法。

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