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A Simple Phenomenological Neuronal Model with Inhibitory and Excitatory Synapses

机译:具有抑制和兴奋突触的简单现象学神经元模型。

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We develop a simple model which simulates neuronal activity as observed in a neuronal network cultivated on a multielectrode array neurochip. The model is based on an inhomogeneous Poisson process to simulate neurons which are active without external input or stimulus as observed in neurochip experiments. Spike train statistics are applied to validate the resulting spike data. Calculated features adapted from spikes and bursts as well as the spike train statistics show that the presented model has potential to simulate neuronal activity.
机译:我们开发了一个简单的模型,可以模拟在多电极阵列神经芯片上培养的神经元网络中观察到的神经元活动。该模型基于不均匀的Poisson过程,以模拟在神经芯片实验中观察到的无外部输入或刺激作用的神经元。应用峰值训练统计数据来验证生成的峰值数据。根据尖峰和爆发以及尖峰序列的统计数据计算得出的特征表明,该模型具有模拟神经元活动的潜力。

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