Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks.
Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks.
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降低率修剪可以优化高效且可靠的分布式网络的构建。
DOI：
10.1371/journal.pcbi.1004347
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发表时间：
2015-07
影响因子：
4.3
通讯作者：
Bar-Joseph Z
中科院分区：
文献类型：
--
作者：
Navlakha S;Barth AL;Bar-Joseph Z
健壮、高效和低成本的网络在生物和工程系统中都具有优势。在大脑的神经网络发育过程中，突触会大量产生，然后随着时间的推移进行修剪。这种策略在设计工程网络时并不常用，因为添加即将删除的连接被认为是浪费。在这里，我们表明，对于大型分布式路由网络，网络功能通过超连通性和积极剪枝得到显著增强，并且全局剪枝率在优化网络结构中起着关键作用，这是一个实验者以前没有研究过的发展参数。我们首先使用高通量图像分析技术来量化哺乳动物新皮质在广泛的发育时间窗口中的剪枝速度，发现随着时间的推移，剪枝速度正在下降。基于这些结果，我们分析了一个计算路由网络模型，并通过理论分析和仿真表明，与其他速率相比，降低速率可以带来更健壮和更高效的网络。我们还给出了该策略在改进航线网络分布式设计方面的应用。因此，来自神经网络形成的灵感建议了设计跨多个领域的分布式网络的有效方法。在大脑神经回路的发育过程中，突触会大量产生，然后随着时间的推移进行修剪。这是一个发生在许多大脑区域和生物体中的基本过程，然而，尽管对这一过程进行了数十年的研究，突触消除的速度以及这种速度如何影响网络的功能和结构还没有被研究过。我们进行了大规模的脑成像实验，以量化发育中的小鼠皮质中突触的消失率，发现突触消失率随着时间的推移而下降(即攻击性消解发生在早期，随后是较长的缓慢消解阶段)。我们证明了这些速率在几种模型下优化了分布式路由网络的效率和稳健性。我们还给出了该策略在改进航空公司网络设计方面的应用。
Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains. During development of neural circuits in the brain, synapses are massively over-produced and then pruned-back over time. This is a fundamental process that occurs in many brain regions and organisms, yet, despite decades of study of this process, the rate of synapse elimination, and how such rates affect the function and structure of networks, has not been studied. We performed large-scale brain imaging experiments to quantify synapse elimination rates in the developing mouse cortex and found that the rate is decreasing over time (i.e. aggressive elimination occurs early, followed by a longer phase of slow elimination). We show that such rates optimize the efficiency and robustness of distributed routing networks under several models. We also present an application of this strategy to improve the design of airline networks.