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Contribution of intrinsic motoneuron properties to discharge hysteresis and its estimation based on paired motor unit recordings: a simulation study

机译:运动神经元固有特性对放电磁滞的贡献及其基于成对电机单元记录的估计:仿真研究

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Motoneuron activity is strongly influenced by the activation of persistent inward currents (PICs) mediated by voltage-gated sodium and calcium channels. However, the amount of PIC contribution to the activation of human motoneurons can only be estimated indirectly. Simultaneous recordings of pairs of motor units have been used to provide an estimate of the PIC contribution by using the firing rate of the lower threshold unit to provide an estimate of the common synaptic drive to both units, and the difference in firing rate (Delta F) of this lower threshold unit at recruitment and de-recruitment of the higher threshold unit to estimate the PIC contribution to activation of the higher threshold unit. It has recently been suggested that a number of factors other than PIC can contribute to Delta F values, including mechanisms underlying spike frequency adaptation and spike threshold accommodation. In the present study, we used a set of compartmental models representing a sample of 20 motoneurons with a range of thresholds to investigate how several different intrinsic motoneuron properties can potentially contribute to variations in Delta F values. We drove the models with linearly increasing and decreasing noisy conductance commands of different rate of rise and duration and determined the influence of different intrinsic mechanisms on discharge hysteresis (the difference in excitatory drive at recruitment and de-recruitment) and Delta F. Our results indicate that, although other factors can contribute, variations in discharge hysteresis and Delta F values primarily reflect the contribution of dendritic PICs to motoneuron activation.
机译:调子隆的活性受电压门控钠和钙通道介导的持续内向电流(PIC)的激活的强烈影响。但是,PIC对人类运动神经元激活的贡献量只能间接估算。成对的电机单元对的同步记录已被用于通过使用下阈值单元的点火率来提供对PIC贡献的估计,以提供对两个单元的共同突触驱动的估计以及点火率的差值(ΔF )在较高阈值单元的募集和取消招募时使用此较低阈值单元,以估算PIC对较高阈值单元激活的贡献。最近,有人提出,除了PIC以外,许多其他因素也可以影响Delta F值,包括尖峰频率适应和尖峰阈值调节的机制。在本研究中,我们使用了一组代表20个运动神经元样本的隔室模型,这些模型具有一定的阈值范围,以研究几种不同的固有运动神经元性质如何可能导致Delta F值的变化。我们使用具有不同上升率和持续时间的噪声电导命令线性增加和减少的模型来驱动模型,并确定了不同内在机制对放电迟滞(补充和取消补充时激励驱动的差异)和Delta F的影响。我们的结果表明尽管其他因素可能会导致这种情况,但放电磁滞和Delta F值的变化主要反映了树枝状PIC对运动神经元活化的影响。

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