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Network of phase-locking oscillators and a possible model for neural synchronization

机译:锁相振荡器网络和神经同步的可能模型

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In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state.
机译:为了建模脑信号的同步,提出了一个三节点的全连接网络。这些节点被认为是电压控制振荡器神经元(VCON),可以推测整个过程如何取决于突触增益,自由运行频率和延迟。以锁相环(PLL)表示的VCON已完全连接,因此出现了渐近稳定的同步状态。在此,导出了同步状态频率的表达式,并讨论了其稳定性的参数依赖性。进行数值模拟,为使用导出公式提供条件。模型微分方程很难进行分析处理,但是一些简化的假设与仿真相结合,为完全连接的VCON网络的长期行为提供了另一种表述。关于这种网络作为大脑频率信号处理的模型,每个PLL代表一个神经元(VCON),提出了它们的同步条件,其中考虑了大脑活动信号的不同频段并将它们与突触增益,延迟和自由运行相关联频率。对于增量波,同步状态在很大程度上取决于延迟。但是,对于alpha,beta和theta波,自由运行的单个频率决定了同步状态。

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