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A system model for investigating passive electrical properties of neurons.

机译:用于研究神经元的被动电特性的系统模型。

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摘要

Passive membrane properties of neurons, characterized by a linear voltage response to constant current stimulation, were investigated by busing a system model approach. This approach utilizes the derived expression for the input impedance of a network, which simulates the passive properties of neurons, to correlate measured intracellular recordings with the response of network models. In this study, the input impedances of different network configurations and of dentate granule neurons, were derived as a function of the network elements and were validated with computer simulations. The parameters of the system model, which are the values of the network elements, were estimated using an optimization strategy. The system model provides for better estimation of the network elements than the previously described signal model, due to its explicit nature. In contrast, the signal model is an implicit function of the network elements which requires intermediate steps to estimate some of the passive properties.
机译:通过总线系统模型方法研究了神经元的被动膜特性,其特征在于对恒定电流刺激的线性电压响应。这种方法利用网络输入阻抗的导出表达式,该表达式模拟神经元的被动特性,以将测得的细胞内记录与网络模型的响应相关联。在这项研究中,不同的网络配置和齿状颗粒神经元的输入阻抗被推导为网络元素的函数,并通过计算机仿真进行了验证。系统模型的参数(即网络元素的值)是使用优化策略进行估算的。由于其明显的特性,与先前描述的信号模型相比,系统模型提供了对网络元素的更好估计。相反,信号模型是网络元素的隐式函数,需要中间步骤才能估计一些无源特性。

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