Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost.
Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost.
复制标题
DOI：
10.1371/journal.pcbi.1005834
复制
发表时间：
2017-11
影响因子：
4.3
通讯作者：
Karbowski J
中科院分区：
文献类型：
--
作者：
Rakowski F;Karbowski J
30年来对线虫连接体的详细了解并没有对我们理解蠕虫的行为做出重大贡献。造成这种情况的主要原因之一是缺乏关于蠕虫连接体中特定神经元之间突触信号类型的数据。这项研究的目的是确定控制运动的小型运动前电路中每个连接的突触极性。即使在这个只有7个神经元的紧凑网络中，所有可能的连接类型(兴奋与抑制)模式的空间也是巨大的。为了有效地处理这一组合问题，我们设计了一种基于遗传算法和大规模并行计算的新的、相对快速的技术，将该技术与神经元间动力学的详细神经生理学模型相结合，并将该理论与现有的行为数据进行了比较。作为这些大规模计算的结果，我们发现与最佳运动数据匹配的最佳连接模式是所有神经元间连接都是抑制的模式，即使那些终止于运动神经元的连接也是如此。这一发现与最近关于线虫胆碱能信号的实验数据一致，表明控制运动的系统是为了节省代谢能量而设计的。此外，这一结果为更真实地建模这些蠕虫的神经控制提供了坚实的基础，并且我们新的强大的计算技术原则上可以应用(可能经过一些修改)到线虫的其他小规模功能电路。神经连接，即神经连接图，对于理解神经系统的设计原则很重要。然而，它们不足以理解网络动力学，而网络动力学又与动物的行为有关。为了理解行为，我们还需要知道神经连接传递的信号类型，或者仅仅是它们的极性(兴奋或抑制)。但这些极性的确定通常是具有挑战性的，因为一个典型的网络中有大量的突触。拥有302个神经元的小线虫秀丽线虫是唯一一种在单个神经元水平上具有已知连接体的动物。在这项研究中，我们使用一种强大而快速的计算技术来优化线虫网络控制运动的内在属性，以确定其连接的信号标志。结果，我们发现所有运动性神经元间联系都是抑制性的，这表明该网络主要通过相互抑制来发挥作用。
The detailed knowledge of C. elegans connectome for 3 decades has not contributed dramatically to our understanding of worm’s behavior. One of main reasons for this situation has been the lack of data on the type of synaptic signaling between particular neurons in the worm’s connectome. The aim of this study was to determine synaptic polarities for each connection in a small pre-motor circuit controlling locomotion. Even in this compact network of just 7 neurons the space of all possible patterns of connection types (excitation vs. inhibition) is huge. To deal effectively with this combinatorial problem we devised a novel and relatively fast technique based on genetic algorithms and large-scale parallel computations, which we combined with detailed neurophysiological modeling of interneuron dynamics and compared the theory to the available behavioral data. As a result of these massive computations, we found that the optimal connectivity pattern that matches the best locomotory data is the one in which all interneuron connections are inhibitory, even those terminating on motor neurons. This finding is consistent with recent experimental data on cholinergic signaling in C. elegans, and it suggests that the system controlling locomotion is designed to save metabolic energy. Moreover, this result provides a solid basis for a more realistic modeling of neural control in these worms, and our novel powerful computational technique can in principle be applied (possibly with some modifications) to other small-scale functional circuits in C. elegans. Neural connectomes, i.e. neural connectivity maps, are important for understanding the design principles of nervous systems. However, they are not sufficient for understanding network dynamics, which in turn are related to animal’s behavior. To understand behavior, we need additionally to know the type of signaling mediated by neural connections, or simply their polarities (excitation or inhibition). But the determination of these polarities is generally challenging because of the large number of synapses in a typical network. The small nematode Caenorhabditis elegans with 302 neurons is the only animal with the known connectome on a level of single neurons. In this study, we use a powerful and fast computational technique to optimize intrinsic properties of C. elegans network controlling locomotion in order to determine the signaling signs of its connections. As a result, we find that all locomotory interneuron connections are inhibitory, which suggests that this network acts mainly via mutual suppression.
登录
查看更多内容
影响因子：
64.8
作者：
Hendricks, Michael;Ha, Heonick;Maffey, Nicolas;Zhang, Yun
通讯作者：
Zhang, Yun
影响因子：
2.5
作者：
Compte, A;Sanchez-Vives, MV;Wang, XJ
通讯作者：
Wang, XJ
DOI：
10.1895/wormbook.1.161.1
发表时间：
2013-08-13
期刊：
WormBook : the online review of C. elegans biology
影响因子：
--
作者：
Hobert, Oliver
通讯作者：
Hobert, Oliver
DOI：
10.1523/jneurosci.4709-11.2012
发表时间：
2012-03-28
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Johnson MD;Hyngstrom AS;Manuel M;Heckman CJ
通讯作者：
Heckman CJ
影响因子：
3.7
作者：
Faumont S;Rondeau G;Thiele TR;Lawton KJ;McCormick KE;Sottile M;Griesbeck O;Heckscher ES;Roberts WM;Doe CQ;Lockery SR
通讯作者：
Lockery SR