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Related Experiment Video

Updated: Nov 23, 2025

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
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Coherence resonance in influencer networks.

Ralf Tönjes1, Carlos E Fiore2, Tiago Pereira3,4

  • 1Institute for Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24, Potsdam, 14476, Germany. toenjes@uni-potsdam.de.

Nature Communications
|January 5, 2021
PubMed
Summary

Adding optimal noise to influencers in complex networks can boost synchronization. This coherence resonance effect in influencer networks highlights the crucial role of network structure in system dynamics.

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Area of Science:

  • Complex Systems Science
  • Network Science
  • Nonlinear Dynamics

Background:

  • Complex networks in nature often feature highly connected nodes called influencers.
  • Influencers play critical roles in network dynamics and structure.
  • The response of influencer networks to external noise is poorly understood.

Purpose of the Study:

  • To investigate the effect of stochastic forcing on oscillatory dynamics in networks with influencers.
  • To explore the phenomenon of coherence resonance in influencer networks.

Main Methods:

  • Analysis of oscillatory dynamics on complex network models.
  • Introduction of controlled stochastic forcing (noise) targeting influencer nodes.
  • Mathematical modeling of network synchronization and response to noise.

Main Results:

  • An optimal level of noise applied to influencers can significantly enhance network synchronization.
  • This effect, termed coherence resonance in influencer networks, is highly nonlinear.
  • Synchronization enhancement is dependent on the interplay between network structure and noise intensity.

Conclusions:

  • The influencer backbone of complex networks can dramatically amplify dynamical responses.
  • Stochasticity, when optimally applied, can be leveraged to improve network function.
  • Findings reveal a novel mechanism for controlling collective behavior in complex systems.