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Frequency preference in two-dimensional neural models: a linear analysis of the interaction between resonant and amplifying currents

机译：二维神经模型中的频率偏好：共振电流和放大电流之间相互作用的线性分析

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Many neuron types exhibit preferred frequency responses in their voltage amplitude (resonance) or phase shift to subthreshold oscillatory currents, but the effect of biophysical parameters on these properties is not well understood. We propose a general framework to analyze the role of different ionic currents and their interactions in shaping the properties of impedance amplitude and phase in linearized biophysical models and demonstrate this approach in a two-dimensional linear model with two effective conductances gL and g1. We compute the key attributes of impedance and phase (resonance frequency and amplitude, zero-phase-frequency, selectivity, etc.) in the gL−g1 parameter space. Using these attribute diagrams we identify two basic mechanisms for the generation of resonance: an increase in the resonance amplitude as g1 increases while the overall impedance is decreased, and an increase in the maximal impedance, without any change in the input resistance, as the ionic current time constant increases. We use the attribute diagrams to analyze resonance and phase of the linearization of two biophysical models that include resonant (Ih or slow potassium) and amplifying currents (persistent sodium). In the absence of amplifying currents, the two models behave similarly as the conductances of the resonant currents is increased whereas, with the amplifying current present, the two models have qualitatively opposite responses. This work provides a general method for decoding the effect of biophysical parameters on linear membrane resonance and phase by tracking trajectories, parametrized by the relevant biophysical parameter, in pre-constructed attribute diagrams.
机译：许多神经元类型在其电压幅度（谐振）或相移到低于阈值的振荡电流方面表现出优选的频率响应，但是生物物理参数对这些特性的影响尚不清楚。我们提出了一个通用框架来分析不同离子电流及其相互作用在线性生物物理模型中塑造阻抗振幅和相位特性方面的作用，并在具有两个有效电导gL和g1的二维线性模型中证明了该方法。我们在gL-g1参数空间中计算了阻抗和相位的关键属性（谐振频率和幅度，零相频率，选择性等）。使用这些属性图，我们确定了产生共振的两种基本机制：随着g1的增加，共振振幅的增加，而总阻抗的降低，以及在不改变输入电阻的情况下，最大阻抗的增加，如离子性的当前时间常数增加。我们使用属性图来分析两个生物物理模型的共振和线性化阶段，这些模型包括共振（Ih或慢钾）和放大电流（持久钠）。在没有放大电流的情况下，两个模型的行为类似，因为谐振电流的电导增加，而在存在放大电流的情况下，两个模型在定性上具有相反的响应。这项工作提供了一种通用方法，可通过在预先构建的属性图中跟踪由相关生物物理参数参数化的轨迹来解码生物物理参数对线性膜共振和相位的影响。

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