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100 1 _ |a Rydin Gorjão, Leonardo
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245 _ _ |a Complexity and irreducibility of dynamics on networks of networks
260 _ _ |a Woodbury, NY
|c 2018
|b American Institute of Physics
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520 _ _ |a We study numerically the dynamics of a network of all-to-all-coupled, identical sub-networks consisting of diffusively coupled, non-identical FitzHugh–Nagumo oscillators. For a large range of within- and between-network couplings, the network exhibits a variety of dynamical behaviors, previously described for single, uncoupled networks. We identify a region in parameter space in which the interplay of within- and between-network couplings allows for a richer dynamical behavior than can be observed for a single sub-network. Adjoining this atypical region, our network of networks exhibits transitions to multistability. We elucidate bifurcations governing the transitions between the various dynamics when crossing this region and discuss how varying the couplings affects the effective structure of our network of networks. Our findings indicate that reducing a network of networks to a single (but bigger) network might not be accurate enough to properly understand the complexity of its dynamics.Many natural systems ranging from ecology to the neurosciences can be described as networks of networks. An example is interacting patches of neural tissue, where each patch constitutes a sub-network. In such a configuration and other models, the sub-networks are often assumed to be identical but consisting of non-identical units. A question arising for such networks of networks is as to what extent their dynamics can be reduced to a more simple network by aggregating parts of the network. We here explore this question by investigating numerically the dynamics of a network of all-to-all-coupled, identical networks consisting of diffusively coupled, non-identical excitable FitzHugh–Nagumo oscillators. Intriguingly, we identify a small region of the parameter space spanned by the within- and between-network coupling strength that allows for a richer dynamical behavior than what can be observed for a single sub-network.
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700 1 _ |a Saha, Arindam
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700 1 _ |a Ansmann, Gerrit
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700 1 _ |a Feudel, Ulrike
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700 1 _ |a Lehnertz, Klaus
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773 _ _ |a 10.1063/1.5039483
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856 4 _ |y Published on 2018-10-08. Available in OpenAccess from 2019-10-08.
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856 4 _ |y Published on 2018-10-08. Available in OpenAccess from 2019-10-08.
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