Nicolaides Christos, Juanes Ruben, Cueto-Felgueroso Luis
Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Sci Rep. 2016 Feb 17;6:21360. doi: 10.1038/srep21360.
Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model-a minimal-ingredients model of nodal activation and interaction within a complex network-is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.
网络组织系统中的自组织和模式形成源于许多相互连接单元的集体激活和相互作用。这些非平衡结构的一个显著特征是它们通常是局部化且稳健的：只有一小部分节点或细胞集合被激活。理解细胞集合作为神经网络和社会技术系统中基本功能单元的作用，已成为网络理论中的一项基本挑战。一个关键的开放性问题是这些基本构建块是如何出现的，以及它们如何运作，从而在复杂网络中连接结构和功能。在这里，我们表明，Swift-Hohenberg连续体模型的网络类似物——一个复杂网络中节点激活和相互作用的最小成分模型——能够产生一系列复杂的局部模式。因此，即使在没有突触强化的情况下，复杂网络中稳健运作的细胞集合的自发形成也可以被解释为自组织的结果。
