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Neural dynamics and bifurcation analysis of piecewise linear neuron models

机译:分段线性神经元模型的神经动力学和分叉分析

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In this paper we study the neural dynamics and bifurcation analysis of easily implementable piecewise linear (PWL) spiking neuron models with membrane potential variables, input current, recovery variables, and parameters describing timescales. Analyses reveal that the models can reproduce six (all) kinds of bifurcation phenomena that are observed in standard biological neuron models. Moreover, these bifurcations are confirmed by time domain simulations, and along with the different phase plane geometries, these qualitative analyses provide explicit tool for the interpretation of different spiking patterns, and to guide parameter selection in PWL neuron models.
机译:在本文中,我们研究了具有膜电位变量,输入电流,恢复变量和描述时标的参数的易于实现的分段线性(PWL)尖峰神经元模型的神经动力学和分叉分析。分析表明,该模型可以重现在标准生物神经元模型中观察到的六种(所有)分叉现象。此外,这些分叉通过时域仿真得到证实,并且随着不同的相平面几何形状,这些定性分析为解释不同的尖峰模式提供了明确的工具,并可以指导PWL神经元模型的参数选择。

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