离子通道调节脊髓运动神经元在有效运动中的招募模型研究。

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Journal of Computational Neuroscience Pub Date : 2020-11-01 Epub Date: 2020-09-08 DOI:10.1007/s10827-020-00763-4
Qiang Zhang, Yue Dai
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引用次数: 4

摘要

在实际运动过程中,猫腰部运动神经元表现出膜特性的变化,包括电压阈值(Vth)、后超极化(AHP)和输入电阻(Rin)的降低以及非线性膜特性的增加。这些变化对运动神经元募集的影响尚不清楚。利用模型方法研究了运动神经元募集的通道机制。根据猫腰部运动神经元的膜特性,构建了慢速(S)、抗疲劳(FR)和快疲劳(FF)三种类型的运动神经元池。模型中包括瞬态钠(NaT)、持久钠(NaP)、延迟整流钾(K(DR))、Ca2+依赖性K+ (K(AHP))和l型钙(CaL)通道。模拟结果表明:(1)加强突触输入会增加三种类型运动神经元的招募数量。(2)增加NaT或NaP或降低K(DR)或K(AHP)降低了spike产生的流变酶,从而增加了运动神经元池的募集。(3) Rin的减少减少了三种类型运动神经元的招募。(4) ff型运动神经元池对突触输入增加、Rin减少、NaT和NaP上调、K(DR)和K(AHP)下调最为敏感,其次为FR-和s型。(5)增加CaL可提高运动神经元池的总放电率,但对招募影响不大。模拟结果表明,离子通道的调节通过调节募集运动神经元的数量或调节运动神经元池的总放电速率来改变运动神经元池的输出。在行走过程中,多种通道通过兴奋性和抑制性突触输入的相互作用促进运动神经元的募集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modeling study of spinal motoneuron recruitment regulated by ionic channels during fictive locomotion.

During fictive locomotion cat lumbar motoneurons exhibit changes in membrane proprieties including a decrease in voltage threshold (Vth), afterhyperpolarization (AHP) and input resistance (Rin) and an increase in non-linear membrane property. The impact of these changes on the motoneuron recruitment remains unknown. Using modeling approach we investigated the channel mechanism regulating the motoneuron recruitment. Three types of motoneuron pools including slow (S), fatigue-resistant (FR) and fast-fatigable (FF) motoneurons were constructed based on the membrane proprieties of cat lumbar motoneurons. The transient sodium (NaT), persistent sodium (NaP), delayed-rectifier potassium [K(DR)], Ca2+-dependent K+ [K(AHP)] and L-type calcium (CaL) channels were included in the models. Simulation results showed that (1) Strengthening synaptic inputs increased the number of recruitments in all three types of motoneurons following the size principle. (2) Increasing NaT or NaP or decreasing K(DR) or K(AHP) lowered rheobase of spike generation thus increased recruitment of motoneuron pools. (3) Decreasing Rin reduced recruitment in all three types of motoneurons. (4) The FF-type motoneuron pool, followed by FR- and S-type, were the most sensitive to increase of synaptic inputs, reduction of Rin, upregulation of NaT and NaP, and downregulation of K(DR) and K(AHP). (5) Increasing CaL enhanced overall discharge rate of motoneuron pools with little effect on the recruitment. Simulation results suggested that modulation of ionic channels altered the output of motoneuron pools with either modulating the number of recruited motoneurons or regulating the overall discharge rate of motoneuron pools. Multiple channels contributed to the recruitment of motoneurons with interaction of excitatory and inhibitory synaptic inputs during walking.

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来源期刊
CiteScore
2.00
自引率
8.30%
发文量
32
审稿时长
3 months
期刊介绍: The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.
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