多层脑网络局部和全局同步过程中的宏观和微观谱特性
Macroscopic and Microscopic Spectral Properties of Multilayer Brain Networks during Local and Global Synchronization
摘要：
我们介绍了一种实用的和计算不要求技术，用于从测量和处理宏观信号中推断网络单元之间在各种微观水平上的相互作用。从网络模型的Kuramoto相振荡器，根据自适应的homophilic和稳态的自适应原则，我们给出的证据表明，增加组内的节点同步（和相应的形成同步集群）也导致碎片整理的小波能量谱的宏观信号。然后，我们的方法被应用于一瞥发生在神经生理系统中的微观相互作用，即，在丘脑-皮质神经网络的癫痫大脑的大鼠，其中组电活动登记通过多通道EEG。我们证明，这是可能的，以推断在不同类型的大脑活动过程中，大脑的相互连接的区域之间的相互作用的程度，并估计区域的参与，在不同层次的意识的产生。
英文摘要：
We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators which evolve adaptively according to homophilic and homeostatic adaptive principles, we give evidence that the increase of synchronization within groups of nodes (and the corresponding formation of synchronous clusters) causes also the defragmentation of the wavelet energy spectrum of the macroscopic signal. Our methodology is then applied for getting a glance to the microscopic interactions occurring in a neurophysiological system, namely, in the thalamo-cortical neural network of an epileptic brain of a rat, where the group electrical activity is registered by means of multichannel EEG. We demonstrate that it is possible to infer the degree of interaction between the interconnected regions of the brain during different types of brain activities, and to estimate the regions' participation in the generation of the different levels of consciousness.
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