Failure of averaging in the construction of a conductance-based neuron model
Failure of averaging in the construction of a conductance-based neuron model
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DOI：
10.1152/jn.00412.2001
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发表时间：
2002-02-01
影响因子：
2.5
通讯作者：
Marder, E
中科院分区：
文献类型：
--
作者：
Golowasch, J;Goldman, MS;Marder, E
生物系统模型的参数通常是通过对许多不同制剂的实验结果进行平均来获得的。为了探索该过程的有效性，我们研究了具有五个电压依赖性电导的基于电导的模型神经元的行为。我们随机改变模型中每个活动电流的最大电导，并确定了生成爆发神经元的最大电导组，这些神经元在缓慢膜电位去极化的峰值处激发单个动作电位。使用该群体的最大电导手段构建的模型本身并不是单尖峰爆发器，而是每次爆发发射三个动作电位。平均失败是因为单尖峰爆发群体的最大电导位于参数空间的高度凹区域，该区域不包含其平均值。这表明多个样本的平均值可能无法表征一个系统，该系统的行为取决于涉及多个高度可变组件的相互作用。
Parameters for models of biological systems are often obtained by averaging over experimental results from a number of different preparations. To explore the validity of this procedure, we studied the behavior of a conductance-based model neuron with five voltage-dependent conductances. We randomly varied the maximal conductance of each of the active currents in the model and identified sets of maximal conductances that generate bursting neurons that fire a single action potential at the peak of a slow membrane potential depolarization. A model constructed using the means of the maximal conductances of this population is not itself a one-spike burster, but rather fires three action potentials per burst. Averaging fails because the maximal conductances of the population of one-spike bursters lie in a highly concave region of parameter space that does not contain its mean. This demonstrates that averages over multiple samples can fail to characterize a system whose behavior depends on interactions involving a number of highly variable components.