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A modification to the Kuramoto model to simulate epileptic seizures as synchronization

机译:对仓本模型的修改,以模拟癫痫发作的同步

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摘要

Abstract The Kuramoto model was developed to describe the coupling of oscillators, motivated by the natural synchronization phenomena. We are interested in modeling an epileptic seizure considering it as the synchronization of action potentials using and modifying this model. In this article, we propose to modify this model, changing the constant coupling force for a function with logistic growth to simulate the onset and epileptic seizure level in an adult male rat caused by the administration of lithium–pilocarpine. Later, we select some frequencies and their respective amplitude values using an algorithm based on the fast Fourier transform (FFT) from an electroencephalography signal when the rat is in basal conditions. Then, we take these values as the natural frequencies of the oscillators in the modified Kuramoto model, considering every oscillator as a single neuron to simulate the emergence of an epileptic seizure numerically by increasing the synchronization value in the coupling function. Finally, using Dynamic Time Warping algorithm, we compare the simulated signal by the Kuramoto model with an FFT approximation of the epileptic seizure.
机译:摘要 Kuramoto模型是针对振子在自然同步现象的驱动下产生的耦合模型。我们有兴趣对癫痫发作进行建模,将其视为使用和修改该模型的动作电位的同步。在本文中,我们建议修改该模型,改变具有逻辑增长的函数的恒定耦合力,以模拟由锂-毛果芸香碱给药引起的成年雄性大鼠的发作和癫痫发作水平。后来,当大鼠处于基础条件下时,我们使用基于快速傅里叶变换(FFT)的算法从脑电图信号中选择一些频率及其各自的振幅值。然后,我们将这些值作为改进的仓本模型中振荡器的固有频率,将每个振荡器视为单个神经元,通过增加耦合函数中的同步值来数值模拟癫痫发作的出现。最后,使用动态时间扭曲算法,将仓本模型的模拟信号与癫痫发作的FFT近似值进行了比较。

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