Rotstein Horacio G
Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ, 07102, USA.
J Comput Neurosci. 2017 Apr;42(2):133-166. doi: 10.1007/s10827-016-0632-6. Epub 2016 Dec 1.
The generation of intrinsic subthreshold (membrane potential) oscillations (STOs) in neuronal models requires the interaction between two processes: a relatively fast positive feedback that favors changes in voltage and a slower negative feedback that opposes these changes. These are provided by the so-called resonant and amplifying gating variables associated to the participating ionic currents. We investigate both the biophysical and dynamic mechanisms of generation of STOs and how their attributes (frequency and amplitude) depend on the model parameters for biophysical (conductance-based) models having qualitatively different types of resonant currents (activating and inactivating) and an amplifying current. Combinations of the same types of ionic currents (same models) in different parameter regimes give rise to different types of nonlinearities in the voltage equation: quasi-linear, parabolic-like and cubic-like. On the other hand, combinations of different types of ionic currents (different models) may give rise to the same type of nonlinearities. We examine how the attributes of the resulting STOs depend on the combined effect of these resonant and amplifying ionic processes, operating at different effective time scales, and the various types of nonlinearities. We find that, while some STO properties and attribute dependencies on the model parameters are determined by the specific combinations of ionic currents (biophysical properties), and are different for models with different such combinations, others are determined by the type of nonlinearities and are common for models with different types of ionic currents. Our results highlight the richness of STO behavior in single cells as the result of the various ways in which resonant and amplifying currents interact and affect the generation and termination of STOs as control parameters change. We make predictions that can be tested experimentally and are expected to contribute to the understanding of how rhythmic activity in neuronal networks emerge from the interplay of the intrinsic properties of the participating neurons and the network connectivity.
在神经元模型中，内在阈下（膜电位）振荡（STOs）的产生需要两个过程之间的相互作用：一个相对快速的正反馈，它有利于电压变化；以及一个较慢的负反馈，它反对这些变化。这些由与参与的离子电流相关的所谓共振和放大门控变量提供。我们研究了STOs产生的生物物理和动力学机制，以及它们的属性（频率和幅度）如何依赖于具有定性不同类型共振电流（激活和失活）和放大电流的生物物理（基于电导）模型的模型参数。在不同参数范围内相同类型离子电流（相同模型）的组合在电压方程中产生不同类型的非线性：准线性、抛物线状和立方状。另一方面，不同类型离子电流（不同模型）的组合可能产生相同类型的非线性。我们研究了由此产生的STOs的属性如何依赖于这些在不同有效时间尺度上运行的共振和放大离子过程的综合效应以及各种类型的非线性。我们发现，虽然一些STO特性和属性对模型参数的依赖性由离子电流的特定组合（生物物理特性）决定，并且对于具有不同此类组合的模型是不同的，但其他特性由非线性类型决定，并且对于具有不同类型离子电流的模型是常见的。我们的结果突出了单细胞中STO行为的丰富性，这是共振和放大电流相互作用以及随着控制参数变化影响STOs产生和终止的各种方式的结果。我们做出了可以通过实验测试的预测，预计这些预测将有助于理解神经元网络中的节律性活动是如何从参与神经元的内在特性和网络连接性的相互作用中产生的。
