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单胺和神经肽连接显著改变了秀丽隐杆线虫连接组的度分布。

Monoamine and neuropeptide connections significantly alter the degree distributions of the Caenorhabditis elegans connectome.

作者信息

Huang Tianxiao, Sun Yan, Zhang Zheng, Deng Shixiong, Peng Rui

机构信息

Departments of aBioinformatics bCell Biology and Medical Genetics cMolecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing, China.

出版信息

Neuroreport. 2017 Nov 8;28(16):1071-1077. doi: 10.1097/WNR.0000000000000875.

Abstract

To understand the behaviors of an individual, it is crucial to understand the neural connections of the nervous system, that is, the connectome. The hermaphrodite Caenorhabditis elegans connectome has served as a prototype for analytical studies since the chemical synapses and gap junctions among the 302 neurons were completely mapped. Recently, monoamine (MA) and neuropeptide (NP) connections were established, which form a multilayer connectome in conjunction with chemical synapses and gap junctions. In this study, we investigated the difference in the in-degree and out-degree distributions, respectively, among the connectomes with and without MA and NP connections. We found that the in-degree and out-degree distributions show different properties of dissimilarity. We discovered that only a few of the degree distributions can be fitted perfectly to power-law or exponential models. Finally, clustering analysis suggests that MA and NP connections significantly alter the degree distributions of the C. elegans connectome. Overall, our study provides an insight into the structural properties of the multilayer connectome with MA and NP connections and confirms the necessity to investigate the multilayer connectome to understand the behaviors of a worm.

摘要

为了理解个体的行为,了解神经系统的神经连接,即连接组,至关重要。自302个神经元之间的化学突触和缝隙连接被完全绘制以来,雌雄同体的秀丽隐杆线虫连接组一直作为分析研究的原型。最近,单胺(MA)和神经肽(NP)连接得以确立,它们与化学突触和缝隙连接共同构成了一个多层连接组。在本研究中,我们分别研究了有和没有MA及NP连接的连接组之间入度分布和出度分布的差异。我们发现入度分布和出度分布呈现出不同的相异性特征。我们发现只有少数度分布能完美拟合幂律或指数模型。最后,聚类分析表明MA和NP连接显著改变了秀丽隐杆线虫连接组的度分布。总体而言,我们的研究为具有MA和NP连接的多层连接组的结构特性提供了见解,并证实了研究多层连接组对于理解线虫行为的必要性。

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