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Toward on-chip functional neuronal networks: Computational study on the effect of synaptic connectivity on neural activity

机译:走向芯片上功能神经元网络:突触连接性对神经活动影响的计算研究

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This paper presents a new unified computational-experimental approach to study the role of the synaptic activity on the activity of neurons in the small neuronal networks (NNs). In a neuronal tissue/organ, this question is investigated with higher complexities by recording action potentials from population of neurons in order to find the relationship between connectivity and the recorded activities. In this approach, we study the dynamics of very small cortical neuronal networks, which can be experimentally synthesized on chip with constrained connectivity. Multi-compartmental Hodgkin-Huxley model is used in NEURON software to reproduce cells by extracting the experimental data from the synthesized NNs. We thereafter demonstrate how the type of synaptic activity affects the network response to specific spike train using the simulation results.
机译:本文提出了一种新的统一的计算实验方法,以研究突触活动对小神经元网络(NNs)中神经元活动的作用。在神经元组织/器官中,通过记录神经元群体的动作电位来寻找连接性与记录的活动之间的关系,从而以更高的复杂度研究了这个问题。在这种方法中,我们研究了非常小的皮质神经元网络的动力学,该动力学可以在具有受限连接性的芯片上通过实验合成。 NEURON软件中使用多隔室Hodgkin-Huxley模型,通过从合成的NN中提取实验数据来复制细胞。此后,我们使用模拟结果演示突触活动的类型如何影响网络对特定尖峰序列的响应。

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