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Chaotic firing in the sinusoidally forced leaky integrate-and-fire model with threshold fatigue

机译:具有阈值疲劳的正弦强迫泄漏积分点火系统中的混沌点火

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The leaky integrate-and-fire (LIF) model is one of the elementary neuronal models that has been widely used to gain understanding of the behavior of many excitable systems. The sinusoidally forced standard leaky integrate-and-fire model reproduces the quasiperiodic and phase locked discharge trains observed experimentally in neurons. However, this basic model fails to generate chaotic firing, whereas this form of behavior has been observed experimentally. We modify the standard LIF through the introduction of threshold fatigue responsible for progressive decrease of excitability during high frequency firing, as observed experimentally. We show that the dynamics of this neuron model under sinusoidal forcing are governed by the iterates of an annulus map and derive expressions for its two characteristic Lyapunov exponents. Using these exponents, it is shown that chaotic dynamics are possible for this model, unlike the standard leaky integrate-and-fire model. Chaotic dynamics occur when memory effects are strong and only under certain forms of threshold fatigue. (C) 2004 Elsevier B.V. All rights reserved.
机译:泄漏集成并发射(LIF)模型是基本神经元模型之一,已被广泛用于了解许多可兴奋系统的行为。正弦强迫标准泄漏积分和发射模型重现了在神经元中实验观察到的准周期和锁相放电序列。但是,此基本模型无法产生混沌激发,而这种行为形式已通过实验观察到。如实验观察到的,我们通过引入阈值疲劳来修改标准LIF,该阈值疲劳导致高频点火过程中的励磁性逐渐降低。我们显示正弦强迫下此神经元模型的动力学是由环空图的迭代控制,并为其两个特征Lyapunov指数导出表达式。使用这些指数,可以证明该模型可能具有混沌动力学特性,这与标准的泄漏集成并发射模型不同。当记忆效应很强且仅在某些形式的阈值疲劳下才会发生混沌动力学。 (C)2004 Elsevier B.V.保留所有权利。

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