title: Chimera-like States in Modular Neural Networks.
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.
authors.affiliation: Crete Center for Quantum Complexity and Nanotechnology, Physics Department, University of Crete, 71003 Heraklion, Greece.|National Center for Scientific Research "Demokritos", 15310 Athens, Greece.
authors.forename: Johanne
authors.initials: J
authors.lastname: Hizanidis
authors.affiliation: Department of Physics, University of Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain.
authors.forename: Nikos E
authors.initials: NE
authors.lastname: Kouvaris
authors.forename: Gorka
authors.initials: G
authors.lastname: Zamora-López
authors.affiliation: Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.|Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
authors.forename: Zamora-López
authors.initials: ZL
authors.lastname: Gorka
authors.affiliation: Department of Physics, University of Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain.
authors.forename: Albert
authors.initials: A
authors.lastname: Díaz-Guilera
authors.affiliation: Department of Mathematical Sciences, University of Essex, Wivenhoe Park, CO4 3SQ Colchester, UK.
authors.forename: Chris G
authors.initials: CG
authors.lastname: Antonopoulos
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000502:physiology*; D063132:Connectome; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology