Keren Naomi, Bar-Yehuda Dan, Korngreen Alon
Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel.
J Physiol. 2009 Apr 1;587(Pt 7):1413-37. doi: 10.1113/jphysiol.2008.167130. Epub 2009 Jan 26.
Constructing physiologically relevant compartmental models of neurones is critical for understanding neuronal activity and function. We recently suggested that measurements from multiple locations along the soma, dendrites and axon are necessary as a data set when using a genetic optimization algorithm to constrain the parameters of a compartmental model of an entire neurone. However, recordings from L5 pyramidal neurones can routinely be performed simultaneously from only two locations. Now we show that a data set recorded from the soma and apical dendrite combined with a parameter peeling procedure is sufficient to constrain a compartmental model for the apical dendrite of L5 pyramidal neurones. The peeling procedure was tested on several compartmental models showing that it avoids local minima in parameter space. Based on the requirements of this analysis procedure, we designed and performed simultaneous whole-cell recordings from the soma and apical dendrite of rat L5 pyramidal neurones. The data set obtained from these recordings allowed constraining a simplified compartmental model for the apical dendrite of L5 pyramidal neurones containing four voltage-gated conductances. In agreement with experimental findings, the optimized model predicts that the conductance density gradients of voltage-gated K(+) conductances taper rapidly proximal to the soma, while the density gradient of the voltage-gated Na(+) conductance tapers slowly along the apical dendrite. The model reproduced the back-propagation of the action potential and the modulation of the resting membrane potential along the apical dendrite. Furthermore, the optimized model provided a mechanistic explanation for the back-propagation of the action potential into the apical dendrite and the generation of dendritic Na(+) spikes.
构建与生理相关的神经元房室模型对于理解神经元活动和功能至关重要。我们最近提出,在使用遗传优化算法来约束整个神经元的房室模型参数时,将来自胞体、树突和轴突多个位置的测量数据作为一个数据集是必要的。然而,从L5锥体神经元常规只能同时在两个位置进行记录。现在我们表明,从胞体和顶端树突记录的数据集结合参数剥离程序足以约束L5锥体神经元顶端树突的房室模型。该剥离程序在几个房室模型上进行了测试,结果表明它避免了参数空间中的局部最小值。基于此分析程序的要求,我们设计并对大鼠L5锥体神经元的胞体和顶端树突进行了同步全细胞记录。从这些记录中获得的数据集允许约束一个简化的包含四种电压门控电导的L5锥体神经元顶端树突的房室模型。与实验结果一致,优化后的模型预测电压门控钾电导的电导密度梯度在靠近胞体处迅速变细,而电压门控钠电导的密度梯度沿顶端树突缓慢变细。该模型再现了动作电位的反向传播以及沿顶端树突静息膜电位的调制。此外,优化后的模型为动作电位向顶端树突的反向传播以及树突钠尖峰的产生提供了一个机理解释。