Flow-Based Network Analysis of the Caenorhabditis elegans Connectome.
Flow-Based Network Analysis of the Caenorhabditis elegans Connectome.
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DOI：
10.1371/journal.pcbi.1005055
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发表时间：
2016-08
影响因子：
4.3
通讯作者：
Barahona M
中科院分区：
文献类型：
--
作者：
Bacik KA;Schaub MT;Beguerisse-Díaz M;Billeh YN;Barahona M
我们利用线虫定向神经元网络上的流量传播来揭示其连接体的动态相关特征。我们在不同的粒度水平上发现了基于流的神经元分组，这与其神经系统的功能和解剖成分有关。对全套单神经元和双神经元消融进行系统的电子计算机评估，以确定导致最严重的多分辨血流结构中断的缺失。这种消融与功能相关的神经元有关，并提示有可能进行进一步的活体研究。此外，我们使用所有尺度上的传入和传出网络流的方向模式来识别连接体中神经元的流特征，而不预先强加先验类别。确定的四个流角色与由生物输入-响应场景激励的信号传播相关联。系统神经科学的目标之一是阐明神经元网络结构和它们实现的功能动力学之间的关系。研究这种相互作用的理想模式生物是线虫，它不仅有一个完整的连接组，而且也是广泛的行为、遗传和神经生理学实验的对象。在这里，我们从动态流动的角度分析线虫的神经网络。我们的分析揭示了网络中信号流的多尺度组织与神经元的解剖和功能特征相联系，以及识别与信号传播相关的不同神经元角色。我们使用我们的计算框架来探索生物输入-响应场景以及在硅消融中的穷尽，这与文献中报告的实验结果有关。
We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios. One of the goals of systems neuroscience is to elucidate the relationship between the structure of neuronal networks and the functional dynamics that they implement. An ideal model organism to study such interactions is the roundworm C. elegans, which not only has a fully mapped connectome, but has also been the object of extensive behavioural, genetic and neurophysiological experiments. Here we present an analysis of the neuronal network of C. elegans from a dynamical flow perspective. Our analysis reveals a multi-scale organisation of the signal flow in the network linked to anatomical and functional features of neurons, as well as identifying different neuronal roles in relation to signal propagation. We use our computational framework to explore biological input-response scenarios as well as exhaustive in silico ablations, which we relate to experimental findings reported in the literature.