White J A, Klink R, Alonso A, Kay A R
Department of Biomedical Engineering, Center for BioDynamics, Boston University, Boston, Massachusetts 02215, USA.
J Neurophysiol. 1998 Jul;80(1):262-9. doi: 10.1152/jn.1998.80.1.262.
Neurons of the superficial medial entorhinal cortex (MEC), which deliver neocortical input to the hippocampus, exhibit intrinsic, subthreshold oscillations with slow dynamics. These intrinsic oscillations, driven by a persistent Na+ current and a slow outward current, may help to generate the theta rhythm, a slow rhythm that plays an important role in spatial and declarative learning. Here we show that the number of persistent Na+ channels underlying subthreshold oscillations is relatively small (<10(4)) and use a physiologically based stochastic model to argue that the random behavior of these channels may contribute crucially to cellular-level responses. In acutely isolated MEC neurons under voltage clamp, the mean and variance of the persistent Na+ current were used to estimate the single channel conductance and voltage-dependent probability of opening. A hybrid stochastic-deterministic model was built by using voltage-clamp descriptions of the persistent and fast-inactivating Na+ conductances, along with the fast and slow K+ conductances. All voltage-dependent conductances were represented with nonlinear ordinary differential equations, with the exception of the persistent Na+ conductance, which was represented as a population of stochastic ion channels. The model predicts that the probabilistic nature of Na+ channels increases the cell's repertoire of qualitative behaviors; although deterministic models at a particular point in parameter space can generate either subthreshold oscillations or phase-locked spikes (but rarely both), models with an appropriate level of channel noise can replicate physiological behavior by generating both patterns of electrical activity for a single set of parameters. Channel noise may contribute to higher order interspike interval statistics seen in vitro with DC current stimulation. Models with channel noise show evidence of spike clustering seen in brain slice experiments, although the effect is apparently not as prominent as seen in experimental results. Channel noise may contribute to cellular responses in vivo as well; the stochastic system has enhanced sensitivity to small periodic stimuli in a form of stochastic resonance that is novel (in that the relevant noise source is intrinsic and voltage-dependent) and potentially physiologically relevant. Although based on a simple model that does not include all known membrane mechanisms of MEC stellate cells, these results nevertheless imply that the stochastic nature of small collections of molecules may have important effects at the cellular and network levels.
内侧内嗅皮层浅层(MEC)的神经元向海马体传递新皮层输入,表现出具有缓慢动力学的内在阈下振荡。这些由持续性钠电流和缓慢外向电流驱动的内在振荡,可能有助于产生θ节律,这是一种在空间和陈述性学习中起重要作用的缓慢节律。在此我们表明,阈下振荡背后的持续性钠通道数量相对较少(<10⁴),并使用基于生理学的随机模型论证这些通道的随机行为可能对细胞水平的反应起关键作用。在电压钳制下急性分离的MEC神经元中,持续性钠电流的均值和方差用于估计单通道电导和电压依赖性开放概率。通过使用持续性和快速失活钠电导以及快速和慢速钾电导的电压钳制描述,构建了一个混合随机 - 确定性模型。所有电压依赖性电导都用非线性常微分方程表示,但持续性钠电导除外,它被表示为一群随机离子通道。该模型预测,钠通道的概率性质增加了细胞定性行为的种类;尽管在参数空间的特定点上确定性模型可以产生阈下振荡或锁相尖峰(但很少同时产生两者),但具有适当水平通道噪声的模型可以通过为单一参数集产生两种电活动模式来复制生理行为。通道噪声可能有助于在体外直流电流刺激下观察到的高阶峰间间隔统计。具有通道噪声的模型显示出在脑片实验中观察到的尖峰聚类证据,尽管这种效应显然不如实验结果中那么显著。通道噪声也可能对体内细胞反应有贡献;随机系统以一种新颖的随机共振形式增强了对小周期刺激的敏感性(因为相关噪声源是内在的且与电压相关),并且可能与生理相关。尽管基于一个不包括MEC星状细胞所有已知膜机制的简单模型,但这些结果仍然意味着少量分子集合的随机性质可能在细胞和网络水平上产生重要影响。