Dudman Joshua T, Nolan Matthew F
Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.
PLoS Comput Biol. 2009 Feb;5(2):e1000290. doi: 10.1371/journal.pcbi.1000290. Epub 2009 Feb 13.
The transformation of synaptic input into patterns of spike output is a fundamental operation that is determined by the particular complement of ion channels that a neuron expresses. Although it is well established that individual ion channel proteins make stochastic transitions between conducting and non-conducting states, most models of synaptic integration are deterministic, and relatively little is known about the functional consequences of interactions between stochastically gating ion channels. Here, we show that a model of stellate neurons from layer II of the medial entorhinal cortex implemented with either stochastic or deterministically gating ion channels can reproduce the resting membrane properties of stellate neurons, but only the stochastic version of the model can fully account for perithreshold membrane potential fluctuations and clustered patterns of spike output that are recorded from stellate neurons during depolarized states. We demonstrate that the stochastic model implements an example of a general mechanism for patterning of neuronal output through activity-dependent changes in the probability of spike firing. Unlike deterministic mechanisms that generate spike patterns through slow changes in the state of model parameters, this general stochastic mechanism does not require retention of information beyond the duration of a single spike and its associated afterhyperpolarization. Instead, clustered patterns of spikes emerge in the stochastic model of stellate neurons as a result of a transient increase in firing probability driven by activation of HCN channels during recovery from the spike afterhyperpolarization. Using this model, we infer conditions in which stochastic ion channel gating may influence firing patterns in vivo and predict consequences of modifications of HCN channel function for in vivo firing patterns.
突触输入转化为动作电位输出模式是一种基本过程，它由神经元所表达的特定离子通道组合决定。尽管单个离子通道蛋白在导通和非导通状态之间进行随机转换这一点已得到充分证实，但大多数突触整合模型都是确定性的，对于随机门控离子通道之间相互作用的功能后果了解相对较少。在此，我们表明，用随机或确定性门控离子通道实现的内嗅皮层II层星状神经元模型，能够重现星状神经元的静息膜特性，但只有随机版本的模型能够完全解释阈下膜电位波动以及在去极化状态下从星状神经元记录到的动作电位输出的簇状模式。我们证明，随机模型实现了一种通过动作电位发放概率的活动依赖性变化来形成神经元输出模式的一般机制。与通过模型参数状态的缓慢变化来产生动作电位模式的确定性机制不同，这种一般随机机制在单个动作电位及其相关的超极化后电位持续时间之外不需要保留信息。相反，在星状神经元的随机模型中，动作电位的簇状模式是由于在动作电位超极化后电位恢复期间HCN通道激活驱动发放概率短暂增加而出现的。利用这个模型，我们推断随机离子通道门控可能影响体内发放模式的条件，并预测HCN通道功能改变对体内发放模式的影响。
