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  Asymmetric adaptivity induces recurrent synchronization in complex networks

Thiele, M., Berner, R., Tass, P. A., Schöll, E., Yanchuk, S. (2023): Asymmetric adaptivity induces recurrent synchronization in complex networks. - Chaos, 33, 2, 023123.
https://doi.org/10.1063/5.0128102

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 Creators:
Thiele, Max1, Author
Berner, Rico1, Author
Tass, Peter A.1, Author
Schöll, Eckehard2, Author              
Yanchuk, Serhiy2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              

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 Abstract: Rhythmic activities that alternate between coherent and incoherent phases are ubiquitous in chemical, ecological, climate, or neural systems. Despite their importance, general mechanisms for their emergence are little understood. In order to fill this gap, we present a framework for describing the emergence of recurrent synchronization in complex networks with adaptive interactions. This phenomenon is manifested at the macroscopic level by temporal episodes of coherent and incoherent dynamics that alternate recurrently. At the same time, the dynamics of the individual nodes do not change qualitatively. We identify asymmetric adaptation rules and temporal separation between the adaptation and the dynamics of individual nodes as key features for the emergence of recurrent synchronization. Our results suggest that asymmetric adaptation might be a fundamental ingredient for recurrent synchronization phenomena as seen in pattern generators, e.g., in neuronal systems. We describe a phenomenon of recurrent synchronization in complex dynamical networks with asymmetric adaptivity. The recurrent synchronization describes a generic mechanism of a repeating abrupt loss and gain of synchronization in complex dynamical networks. From an applied perspective, our results show how adaptation mechanisms can play a fundamental role for pattern generators, e.g., in neuronal systems. Methodologically, we present a framework for studying complex temporal patterns in adaptive dynamical networks. This mechanisms might be relevant for the understanding of the pathophysiology of Parkinsonian resting tremor and other impaired central pattern generators.

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Language(s): eng - English
 Dates: 2023-02-152023-02-15
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0128102
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Adaptation
Research topic keyword: Complex Networks
Research topic keyword: Health
Research topic keyword: Nonlinear Dynamics
OATYPE: Hybrid - American Institute of Physics
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 33 (2) Sequence Number: 023123 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)