Beyond two-cell networks: Experimental measurement of neuronal responses to multiple synaptic inputs
Beyond two-cell networks: Experimental measurement of neuronal responses to multiple synaptic inputs
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DOI：
10.1007/s10827-005-0336-9
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发表时间：
2005-06-01
影响因子：
1.2
通讯作者：
White, JA
中科院分区：
文献类型：
--
作者：
Netoff, TI;Acker, CD;White, JA
大量神经元的振荡被认为对大脑的正常功能很重要。我们已经使用相位响应曲线（PRC）的方法来表征单神经元的动态和预测人口动态。我们过去的实验工作仅限于特殊情况（例如，2-周期性放电神经元的细胞网络）。在这里，我们探索的可行性，扩展我们的方法来预测在更广泛的条件下，大鼠内嗅皮层的星状细胞（SC）的同步特性。特别是，我们测试的假设，PRCs在SC的规模与突触振幅的变化呈线性关系，以及测量如何响应泊松过程驱动的输入可以预测PRCs。虽然我们看到非线性响应的兴奋性和抑制性的输入，我们发现，模型的基础上弱耦合占缩放和泊松过程驱动的输入相当准确。
Oscillations of large populations of neurons are thought to be important in the normal functioning of the brain. We have used phase response curve (PRC) methods to characterize the dynamics of single neurons and predict population dynamics. Our past experimental work was limited to special circumstances (e.g., 2-cell networks of periodically firing neurons). Here, we explore the feasibility of extending our methods to predict the synchronization properties of stellate cells (SCs) in the rat entorhinal cortex under broader conditions. In particular, we test the hypothesis that PRCs in SCs scale linearly with changes in synaptic amplitude, and measure how well responses to Poisson process-driven inputs can be predicted in terms of PRCs. Although we see nonlinear responses to excitatory and inhibitory inputs, we find that models based on weak coupling account for scaling and Poisson process-driven inputs reasonably accurately.