Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression

机译：具有动态阈值和短期突触抑制的LiF neuron的输入 - 输出特性

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We consider a model of leaky integrate-and-fire neuron with dynamic threshold and a very simple realization of short term synaptic depression mechanism. Model simplicity makes possible creation of very large networks on its basis. Required general properties of these networks can be obtained due to the appropriate selection of neuron parameters. Knowledge of the dependence of neuron firing frequency on presynaptic activity for various neuron parameters is crucial for this selection. Since this dependence cannot be obtained in an exact analytical form we describe the process of building its empirical approximation using the multiple adaptive regression splines algorithm. This methodology can be used for other neuron models.

机译：我们考虑一种漏水集成和灭火神经元的模型，具有动态阈值，简单地实现了短期突触抑制机制。模型简单性可以在其基础上创建非常大的网络。 Required general properties of these networks can be obtained due to the appropriate selection of neuron parameters.知识神经元烧制频率对各种神经元参数的突触前活性的依赖性对该选择至关重要。由于这种依赖性不能以精确的分析形式获得，因此我们描述了使用多元自适应回归算法构建其经验逼近的过程。该方法可用于其他神经元模型。

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《International Workshop on Artificial Neural Networks and Intelligent Information Processing》|2014年||共8页
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Mikhail Kiselev;
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2. Glycine inhibits startle-mediating neurons in the caudal pontine reticular formation but is not involved in synaptic depression underlying short-term habituation of startle. [J] . Geis HR, Schmid S Neuroscience Research: The Official Journal of the Japan Neuroscience Society . 2011,第2期

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4. Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression [C] . Mikhail Kiselev International Workshop on Artificial Neural Networks and Intelligent Information Processing . 2014

机译：具有动态阈值和短期突触抑制的LiF neuron的输入 - 输出特性
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Input-output Characteristics of LIF Neuron with Dynamic Threshold and Short Term Synaptic Depression

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