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A Study on Patterns of Neural Activity Generation from A Bio-realistic Cerebellum Neural Network

机译:生物现实脑神经网络从神经活性的模式研究

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The biological neural network signal flow is a complex process and difficult to interpret. The purpose of this study is to build a model of a simplified cerebellum neural network and investigate its working behavior in generating neuronal patterns. The model is constructed by referring to the neural anatomic structure of the mammal cerebellum and then simulated using Matlab Simulink software. The artificial neural network dimension is much smaller than the size of the real cerebellar neural network in mammal due to hardware simulation resource limitation. Thus, the utilization of extensivescale spiking neural networks is limited due to the grown of computational costs associated with propagating bio-realistic neural models. The parameters correlated with the neuron function also affect the biological plausibility of the spiking neural network. At the conclusion, we present the pattern generation of a cerebellum- like neural network and briefly explained why such patterns are generated.
机译:生物网络信号流是复杂的过程,难以解释。本研究的目的是构建简化的小脑神经网络的模型,并研究其在产生神经元模式时的工作行为。该模型是通过参考哺乳动物小脑的神经解剖结构来构建,然后使用MATLAB Simulink软件模拟。由于硬件仿真资源限制,人工神经网络维度远小于哺乳动物中真正的大脑神经网络的大小。因此,由于与传播生物逼真神经模型相关的计算成本增加,利用扩展峰值尖峰神经网络的利用受到限制。与神经元功能相关的参数也影响了尖峰神经网络的生物合理性。在结论中,我们介绍了小脑类似的神经网络的模式生成,并简要解释了为什么产生这种模式。

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