Self-organization of network dynamics into local quantized states
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Nicolaides-2016-Self-organization.pdf
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1.02 MB
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Author(s)
Nicolaides, Christos
Juanes, Ruben
Cueto-Felgueroso, Luis
Date Issued
February 2016
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Nicolaides, Christos, Ruben Juanes, and Luis Cueto-Felgueroso. “Self-Organization of Network Dynamics into Local Quantized States.” Scientific Reports 6 (February 17, 2016): 21360.
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Sloan School of Management
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1038/srep21360
