Dresden 2017 – wissenschaftliches Programm
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DY: Fachverband Dynamik und Statistische Physik
DY 63: Controlling Complex Networks in Nature and Engineering (Focus session, joint DY/SOE/BP)
DY 63.3: Vortrag
Freitag, 24. März 2017, 10:30–10:45, ZEU 160
Coherence-Resonance Chimeras in a Neural Network — •Anna Zakharova1, Nadezhda Semenova2, Vadim Anishchenko2, and Eckehard Schöll1 — 1Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin, Germany — 2Department of Physics, Saratov State University, Astrakhanskaya street 83, 410012 Saratov, Russia
We show that chimera patterns can be induced by noise in nonlocally coupled neural networks in the excitable regime. In contrast to classical chimeras, occurring in noise-free oscillatory networks, they have features of two phenomena: coherence resonance and chimera states. Therefore, we call them coherence-resonance chimeras [1]. These patterns demonstrate the constructive role of noise and appear for intermediate values of noise intensity, which is a characteristic feature of coherence resonance. In the coherence-resonance chimera state a neural network of identical elements splits into two coexisting domains with different behavior: spatially coherent and spatially incoherent, a typical property of chimera states. Moreover, these noise-induced chimera states are characterized by alternating behavior: coherent and incoherent domains switch periodically their location. We show that this alternating switching can be explained by analyzing the coupling functions.
[1] N. Semenova, A. Zakharova, V. Anishchenko, E. Schöll, Coherence-resonance chimeras in a network of excitable elements, Phys. Rev. Lett. 117, 014102 (2016)