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Title: Self-organization of network dynamics into local quantized states

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. Thus, 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.
 [1] ;  [1] ;  [2]
  1. Massachusetts Institute of Technology, Cambridge, MA (United States)
  2. Massachusetts Institute of Technology, Cambridge, MA (United States); Univ. of Madrid (Spain)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 6; Journal ID: ISSN 2045-2322
Nature Publishing Group
Research Org:
Massachusetts Institute of Technology, Cambridge, MA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
59 BASIC BIOLOGICAL SCIENCES; complex networks; information theory and computation
OSTI Identifier: