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Title: Chimera-like states in modular neural networks
Author: Hizanidis, Johanne
Kouvaris, Nikos E.
Zamora López, Gorka
Díaz Guilera, Albert
Antonopoulos, Chris G.
Keywords: Xarxes neuronals (Informàtica)
Conducta (Psicologia)
Simulació per ordinador
Sistema nerviós
Neural networks (Computer science)
Human behavior
Computer simulation
Nervous system
Issue Date: 22-Jan-2016
Publisher: Nature Publishing Group
Abstract: Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey chaotic bursting dynamics. Neurons are assumed to be connected with electrical synapses within their communities and with chemical synapses across them. As our numerical simulations reveal, the coaction of these two types of coupling can shape the dynamics in such a way that chimera-like states can happen. They consist of a fraction of synchronized neurons which belong to the larger communities, and a fraction of desynchronized neurons which are part of smaller communities. In addition to the Kuramoto order parameter ρ, we also employ other measures of coherence, such as the chimera-like χ and metastability λ indices, which quantify the degree of synchronization among communities and along time, respectively. We perform the same analysis for networks that share common features with the C. elegans neural network. Similar results suggest that under certain assumptions, chimera-like states are prominent phenomena in modular networks, and might provide insight for the behavior of more complex modular networks.
Note: Reproducció del document publicat a:
It is part of: Scientific Reports, 2016, vol. 6, p. 19845
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ISSN: 2045-2322
Appears in Collections:Articles publicats en revistes (Física de la Matèria Condensada)

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