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首页> 外文期刊>Neural computation >Statistical Computer Model Analysis of the Reciprocal and Recurrent Inhibitions of the Ia-EPSP in α-Motoneurons
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Statistical Computer Model Analysis of the Reciprocal and Recurrent Inhibitions of the Ia-EPSP in α-Motoneurons

机译：I-EPSP在α-单质子神经中的互作和反复抑制的统计计算机模型分析

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摘要

We simulate the inhibition of Ia-glutamatergic excitatory postsynaptic potential (EPSP) by preceding it with glycinergic recurrent (REN) and reciprocal (REC) inhibitory postsynaptic potentials (IPSPs). The inhibition is evaluated in the presence of voltage-dependent conductances of sodium, delayed rectifier potassium, and slow potassium in five α-motoneurons (MNs). We distribute the channels along the neuronal dendrites using, alternatively, a density function of exponential rise (ER), exponential decay (ED), or a step function (ST). We examine the change in EPSP amplitude, the rate of rise (RR), and the time integral (TI) due to inhibition. The results yield six major conclusions. First, the EPSP peak and the kinetics depending on the time interval are either amplified or depressed by the REC and REN shunting inhibitions. Second, the mean EPSP peak, its TI, and RR inhibition of ST, ER, and ED distributions turn out to be similar for analogous ranges of G. Third, for identical G, the large variations in the parameters' values can be attributed to the sodium conductance step (g_(Na-step)) and the active dendritic area. We find that small g_(Na_step) on a few dendrites maintains the EPSP peak, its TI, and RR inhibition similar to the passive state, but high g_(Na_step) on many dendrites decrease the inhibition and sometimes generates even an excitatory effect. Fourth, the MN's input resistance does not alter the efficacy of EPSP inhibition. Fifth, the REC and REN inhibitions slightly change the EPSP peak and its RR. However, EPSP TI is depressed by the REN inhibition more than the REC inhibition. Finally, only an inhibitory effect shows up during the EPSP TI inhibition, while there are both inhibitory and excitatory impacts on the EPSP peak and its RR.
机译：我们通过先于甘氨酸复发性（REN）和相互（REC）抑制性突触后电位（IPSPs）来模拟对Ia-谷氨酸能兴奋性突触后电位（EPSP）的抑制。在五个α-运动神经元（MNs）中存在钠，延迟的整流钾和慢钾的电压依赖性电导的情况下评估抑制作用。我们沿神经元树突分布通道，或者使用指数上升（ER），指数衰减（ED）或阶跃函数（ST）的密度函数。我们检查了由于抑制而导致的EPSP振幅，上升率（RR）和时间积分（TI）的变化。结果得出六个主要结论。首先，RECP和REN分流抑制会放大或抑制EPSP峰和取决于时间间隔的动力学。第二，对于相似的G范围，平均EPSP峰，其对ST，ER和ED分布的TI和RR抑制作用相似。第三，对于相同的G，参数值的较大变化可归因于钠电导步骤（g_（Na-step））和有效的树突区域。我们发现，少数树突上的小g_（Na_step）保持类似于被动状态的EPSP峰，其TI和RR抑制作用，但许多树突上的高g_（Na_step）则降低了抑制作用，有时甚至产生兴奋作用。第四，MN的输入电阻不会改变EPSP抑制的功效。第五，REC和REN抑制会稍微改变EPSP峰及其RR。但是，与REC抑制相比，REN抑制对EPSP TI的抑制更大。最后，在EPSP TI抑制过程中仅显示抑制作用，而对EPSP峰及其RR既有抑制作用又有兴奋作用。

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  • 来源
    《Neural computation》 |2013年第1期|75-100|共26页
  • 作者

    G. Gradwohl; Y. Grossman;

  • 作者单位

    Department of Physiology, Faculty of Health Sciences, and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel, and Unit of Biomedical Engineering, Department of Physics, Jerusalem College of Technology, Jerusalem, 91160, Israel;

    Department of Physiology, Faculty of Health Sciences, and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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