Caenorhabditis elegans and the network control framework—FAQs
Caenorhabditis elegans and the network control framework—FAQs
复制标题
DOI：
10.1098/rstb.2017.0372
复制
发表时间：
2018-05
期刊：
影响因子：
--
通讯作者：
Emma K. Towlson;P. Vértes;Gang Yan;Yee Lian Chew;Denise S Walker;W. Schafer;A. Barabási
中科院分区：
文献类型：
--
作者：
Emma K. Towlson;P. Vértes;Gang Yan;Yee Lian Chew;Denise S Walker;W. Schafer;A. Barabási
控制对于任何神经系统的功能都是必不可少的。事实上，在健康的条件下，大脑必须能够在系统的输入和输出之间持续保持严密的功能控制。因此，人们可能会假设，大脑的线路是由维持对多个尺度的控制、维持关键内部变量的稳定性以及根据环境线索产生行为的需要预先决定的。网络控制的最新进展为探索复杂生物、社会和技术网络中的结构-功能关系提供了一个强大的数学框架，并开始对神经元系统产生重要而精确的见解。网络控制范式承诺一个预测的、定量的框架来统一不同的数据集，以充分描述神经系统，并为观察到的结构和功能关系提供机制解释。在这里，我们对秀丽隐杆线虫的网络控制框架进行了全面的回顾（Yan et al. 2017 Nature 550, 519-523）。（doi:10.1038/nature24056）)，以常见问题的形式。我们介绍了网络控制的理论、计算和实验方面，并讨论了其当前的能力和局限性，以及下一个可能的进展和改进。我们进一步提供Python代码，以便能够以特定于该原型生物体的方式探索控制原理。这篇文章是讨论会议“连接组行为：在细胞分辨率上模拟秀丽隐杆线虫”的一部分。
Control is essential to the functioning of any neural system. Indeed, under healthy conditions the brain must be able to continuously maintain a tight functional control between the system's inputs and outputs. One may therefore hypothesize that the brain's wiring is predetermined by the need to maintain control across multiple scales, maintaining the stability of key internal variables, and producing behaviour in response to environmental cues. Recent advances in network control have offered a powerful mathematical framework to explore the structure–function relationship in complex biological, social and technological networks, and are beginning to yield important and precise insights on neuronal systems. The network control paradigm promises a predictive, quantitative framework to unite the distinct datasets necessary to fully describe a nervous system, and provide mechanistic explanations for the observed structure and function relationships. Here, we provide a thorough review of the network control framework as applied to Caenorhabditis elegans (Yan et al. 2017 Nature 550, 519–523. (doi:10.1038/nature24056)), in the style of Frequently Asked Questions. We present the theoretical, computational and experimental aspects of network control, and discuss its current capabilities and limitations, together with the next likely advances and improvements. We further present the Python code to enable exploration of control principles in a manner specific to this prototypical organism. This article is part of a discussion meeting issue ‘Connectome to behaviour: modelling C. elegans at cellular resolution’.