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识别维持爆发活动的关键参数相关性。

Identifying crucial parameter correlations maintaining bursting activity.

机构信息

Department of Biology, Emory University, Atlanta, Georgia, United States of America.

出版信息

PLoS Comput Biol. 2014 Jun 19;10(6):e1003678. doi: 10.1371/journal.pcbi.1003678. eCollection 2014 Jun.

Abstract

Recent experimental and computational studies suggest that linearly correlated sets of parameters (intrinsic and synaptic properties of neurons) allow central pattern-generating networks to produce and maintain their rhythmic activity regardless of changing internal and external conditions. To determine the role of correlated conductances in the robust maintenance of functional bursting activity, we used our existing database of half-center oscillator (HCO) model instances of the leech heartbeat CPG. From the database, we identified functional activity groups of burster (isolated neuron) and half-center oscillator model instances and realistic subgroups of each that showed burst characteristics (principally period and spike frequency) similar to the animal. To find linear correlations among the conductance parameters maintaining functional leech bursting activity, we applied Principal Component Analysis (PCA) to each of these four groups. PCA identified a set of three maximal conductances (leak current, [Formula: see text]Leak; a persistent K current, [Formula: see text]K2; and of a persistent Na+ current, [Formula: see text]P) that correlate linearly for the two groups of burster instances but not for the HCO groups. Visualizations of HCO instances in a reduced space suggested that there might be non-linear relationships between these parameters for these instances. Experimental studies have shown that period is a key attribute influenced by modulatory inputs and temperature variations in heart interneurons. Thus, we explored the sensitivity of period to changes in maximal conductances of [Formula: see text]Leak, [Formula: see text]K2, and [Formula: see text]P, and we found that for our realistic bursters the effect of these parameters on period could not be assessed because when varied individually bursting activity was not maintained.

摘要

最近的实验和计算研究表明,线性相关的参数集(神经元的内在和突触特性)允许中枢模式生成网络产生和维持其节奏活动,而不受内部和外部条件变化的影响。为了确定相关电导在功能爆发活动的稳健维持中的作用,我们使用了我们现有的水蛭心跳 CPG 的半中心振荡器 (HCO) 模型实例的数据库。从数据库中,我们确定了爆发器(孤立神经元)和半中心振荡器模型实例的功能活动组,以及每个组的现实亚组,这些亚组显示出与动物相似的爆发特征(主要是周期和尖峰频率)。为了找到维持功能性水蛭爆发活动的电导参数之间的线性相关性,我们对这四个组中的每一个都应用了主成分分析 (PCA)。PCA 确定了一组三个最大电导(泄漏电流,[公式:见文本]Leak;持久 K 电流,[公式:见文本]K2;和持久 Na+电流,[公式:见文本]P),这组电导对于爆发器实例的两个组是线性相关的,但对于 HCO 组则不是。HCO 实例在降维空间中的可视化表明,对于这些实例,这些参数之间可能存在非线性关系。实验研究表明,周期是受调制输入和心内神经元温度变化影响的关键属性。因此,我们探索了最大电导 [公式:见文本]Leak、[公式:见文本]K2 和 [公式:见文本]P 的变化对周期的敏感性,我们发现对于我们的现实爆发器,由于个体变化时爆发活动无法维持,因此无法评估这些参数对周期的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6262/4063674/41283419a766/pcbi.1003678.g001.jpg

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