History-dependent dynamics in a generic model of ion channels - an analytic study
History-dependent dynamics in a generic model of ion channels - an analytic study
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DOI：
10.3389/fncom.2010.00003
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发表时间：
2010-03-01
影响因子：
3.2
通讯作者：
Meir, Ron
中科院分区：
文献类型：
--
作者：
Soudry, Daniel;Meir, Ron
最近的实验表明，单个神经元和离子通道群对刺激的适应时间尺度随着刺激长度的增加而减慢；事实上，在这样的系统中似乎不存在时间尺度的上界。此外，在单离子通道上的膜片钳实验暗示了在单个离子通道内存在较大的、大多数是不可观察的失活状态空间。这就提出了大量失活状态与观察到的行为之间关系的问题。在这项工作中，我们提出了一个离子通道动力学的最小模型，它不假设任何特定的失活状态空间结构。这个模型很简单，可以进行分析研究。这导致了一个清晰而简洁的解释，实验观察到的指数历史依赖性弛豫钠通道在电压箝位设置，并表明他们的恢复速率从缓慢失活必须电压依赖。此外，我们预测历史依赖的松弛不能由过于稀疏的尖峰活动产生。虽然该模型是在考虑离子通道种群的情况下创建的，但它的简单性和通用性使其成为在其他系统中建模类似效果的良好起点，并且可以扩展到更高的级别，例如已知具有多个时间尺度的单个神经元。
Recent experiments have demonstrated that the timescale of adaptation of single neurons and ion channel populations to stimuli slows down as the length of stimulation increases; in fact, no upper bound on temporal timescales seems to exist in such systems. Furthermore, patch clamp experiments on single ion channels have hinted at the existence of large, mostly unobservable, inactivation state spaces within a single ion channel. This raises the question of the relation between this multitude of inactivation states and the observed behavior. In this work we propose a minimal model for ion channel dynamics which does not assume any specific structure of the inactivation state space. The model is simple enough to render an analytical study possible. This leads to a clear and concise explanation of the experimentally observed exponential history-dependent relaxation in sodium channels in a voltage clamp setting, and shows that their recovery rate from slow inactivation must be voltage dependent. Furthermore, we predict that history-dependent relaxation cannot be created by overly sparse spiking activity. While the model was created with ion channel populations in mind, its simplicity and genericalness render it a good starting point for modeling similar effects in other systems, and for scaling up to higher levels such as single neurons which are also known to exhibit multiple time scales.