Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems.
Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems.
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DOI：
10.1371/journal.pcbi.0020095
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发表时间：
2006-07-21
影响因子：
4.3
通讯作者：
Hilgetag, Claus C
中科院分区：
文献类型：
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作者：
Kaiser, Marcus;Hilgetag, Claus C
有人建议，几个组织范围内的神经系统显示出最佳的组件放置，其中任何空间重排将导致总线的增加。使用广泛的连接数据集用于不同的神经网络以及网络节点的空间坐标结合使用，我们将优化算法应用于网络布局，以搜索节省电线组件的重排。我们发现，在所有测试的神经网络中，优化的组件重排可以大大降低总线长度。具体而言，95个灵长类动物（猕猴）皮质区域之间的总线可能会降低32％，并且在全球范围内，线虫秀丽隐杆线虫中神经元网络的接线可能会降低48％，而额叶神经节内的神经元在49％的水平上可以降低49％。由于神经网络中存在长距离投影，因此可能会减小接线长度。我们通过将原始网络与具有相同大小的最小重新连接的网络进行比较，探讨了这些预测的作用，该网络仅具有最短的连接。在最低限时的网络中，与原始网络相比，组件之间最短路径的处理步骤数量显着增加。其他基准比较还表明，神经网络与最小化处理路径长度而不是接线长度的网络布局更相似。这些发现表明，神经系统不是针对最小全球接线的优化，而是针对各种因素，包括最小化处理步骤。
什么限制塑造了神经网络的组织和空间布局？理论神经科学中的一个有影响力的想法是，神经网络的整体布线应尽可能短。例如，可以通过连接的网络组件的最佳空间布置来实现电线。作者评估了两个代表性系统中的组件放置优化概念，即秀丽隐杆线虫蠕虫的神经元网络和灵长类动物大脑的远距离皮质连接。与以前的结果相反，他们发现许多网络布局的总接线比原始的生物网络要短得多。这种非最佳组件放置源于网络中的长距离连接。这种联系可能以发展和代谢成本来实现。但是，正如本文中的分析所示，它们还有助于减少网络中的信号处理步骤的数量。因此，神经网络的组织是由多个约束的权衡取舍的，其中包括总线长度和处理步骤的平均数量。
It has been suggested that neural systems across several scales of organization show optimal component placement, in which any spatial rearrangement of the components would lead to an increase of total wiring. Using extensive connectivity datasets for diverse neural networks combined with spatial coordinates for network nodes, we applied an optimization algorithm to the network layouts, in order to search for wire-saving component rearrangements. We found that optimized component rearrangements could substantially reduce total wiring length in all tested neural networks. Specifically, total wiring among 95 primate (Macaque) cortical areas could be decreased by 32%, and wiring of neuronal networks in the nematode Caenorhabditis elegans could be reduced by 48% on the global level, and by 49% for neurons within frontal ganglia. Wiring length reductions were possible due to the existence of long-distance projections in neural networks. We explored the role of these projections by comparing the original networks with minimally rewired networks of the same size, which possessed only the shortest possible connections. In the minimally rewired networks, the number of processing steps along the shortest paths between components was significantly increased compared to the original networks. Additional benchmark comparisons also indicated that neural networks are more similar to network layouts that minimize the length of processing paths, rather than wiring length. These findings suggest that neural systems are not exclusively optimized for minimal global wiring, but for a variety of factors including the minimization of processing steps. What constraints shape the organization and spatial layout of neural networks? One influential idea in theoretical neuroscience has been that the overall wiring of neural networks should be as short as possible. Wire-saving could be achieved, for instance, through an optimal spatial arrangement of the connected network components. The authors evaluated this concept of component placement optimization in two representative systems, the neuronal network of the Caenorhabditis elegans worm and the long-range cortical connections of the primate brain. Contrary to previous results, they found many network layouts with substantially shorter total wiring than that of the original biological networks. This nonoptimal component placement arose from the existence of long-distance connections in the networks. Such connections may come at a developmental and metabolic cost; however, as the analyses reported in this article show, they also help to reduce the number of signal processing steps across the networks. Therefore, the organization of neural networks is shaped by trade-offs from multiple constraints, among them total wiring length and the average number of processing steps.