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The Approach to Modeling of Synchronized Bursting in Neuronal Culture Using a Mathematical Model of a Neuron with Autoregulation Mechanism

机译:用自动调节机制使用神经元数学模型建模神经元培养中同步爆裂的方法

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The paper presents mathematical model of spike activity of a neuronal culture which exhibits bursting behavior—synchronized spontaneous packs of population activity. Neuron in the developed neural network model is a modification of Leaky Integrate-and-Fire neuron. The neuron model acquires a new quality due to the introduction of two new neuron state variables—"resource" and "strength". The new learning mechanism for synaptic weights is proposed. It assumes dependence of weight corrections from the intensity of spike activity of presynaptic neurons for a previous time interval. The model experiment shows the ability of the neural network based on the proposed model of neurons, to produce bursting activity. Setting of neuron model parameters makes it possible to obtain bursts with various characteristics. The results of model simulation are presented. The prospects for applying the model to study the mechanisms of learning in neuronal cultures in vitro are discussed.
机译:本文介绍了神经元培养的尖峰活动的数学模型,其表现出突发行为同步的人口活性。发发的神经网络模型中的神经元是一种渗漏整合和火神经元的修改。由于引入了两个新的神经元状态变量 - “资源”和“力量”,神经元模型由于引入了新的质量。提出了突触权重的新学习机制。它假设重量校正的依赖性校正从突触前神经元的峰值活性的强度进行前一次时间间隔。模型实验表明了神经网络基于所提出的神经元模型的能力,以产生爆破活动。 Neuron模型参数的设置使得可以获得具有各种特性的突发。提出了模型模拟的结果。讨论了应用模型研究体外学习学习机制的前景。

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