Helen Wills Neuroscience Institute and Department of Psychology, University of California Berkeley, 132 Barker Hall Berkeley, Berkeley, CA, 94720, USA.
Department of Bioengineering, University of Pennsylvania, Hayden Hall 318C, Philadelphia, PA, 19104, USA.
Nat Commun. 2017 Nov 2;8(1):1277. doi: 10.1038/s41467-017-01189-w.
A complex system can be represented and analyzed as a network, where nodes represent the units of the network and edges represent connections between those units. For example, a brain network represents neurons as nodes and axons between neurons as edges. In many networks, some nodes have a disproportionately high number of edges as well as many edges between each other and are referred to as the "rich club". In many different networks, the nodes of this club are assumed to support global network integration. Here we show that another set of nodes, which have edges diversely distributed across the network, form a "diverse club". The diverse club exhibits, to a greater extent than the rich club, properties consistent with an integrative network function-these nodes are more highly interconnected and their edges are more critical for efficient global integration. Finally, these two clubs potentially evolved via distinct selection pressures.
复杂系统可以表示和分析为网络,其中节点代表网络的单元,边代表这些单元之间的连接。例如,大脑网络将神经元表示为节点,将神经元之间的轴突表示为边。在许多网络中,一些节点具有不成比例的高数量的边以及彼此之间的许多边,并且被称为“富俱乐部”。在许多不同的网络中,这个俱乐部的节点被认为支持全局网络集成。在这里,我们表明另一组节点,其边在网络中分布广泛,形成了一个“多样俱乐部”。多样俱乐部表现出比富俱乐部更大程度的整合网络功能的特性——这些节点具有更高的连接性,它们的边对于有效的全局整合更为关键。最后,这两个俱乐部可能是通过不同的选择压力进化而来的。