Literature DB >> 33398017

Coherence resonance in influencer networks.

Ralf Tönjes1, Carlos E Fiore2, Tiago Pereira3,4.   

Abstract

Complex networks are abundant in nature and many share an important structural property: they contain a few nodes that are abnormally highly connected (hubs). Some of these hubs are called influencers because they couple strongly to the network and play fundamental dynamical and structural roles. Strikingly, despite the abundance of networks with influencers, little is known about their response to stochastic forcing. Here, for oscillatory dynamics on influencer networks, we show that subjecting influencers to an optimal intensity of noise can result in enhanced network synchronization. This new network dynamical effect, which we call coherence resonance in influencer networks, emerges from a synergy between network structure and stochasticity and is highly nonlinear, vanishing when the noise is too weak or too strong. Our results reveal that the influencer backbone can sharply increase the dynamical response in complex systems of coupled oscillators.

Entities:  

Year:  2021        PMID: 33398017     DOI: 10.1038/s41467-020-20441-4

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  25 in total

1.  Heterogeneity in oscillator networks: are smaller worlds easier to synchronize?

Authors:  Takashi Nishikawa; Adilson E Motter; Ying-Cheng Lai; Frank C Hoppensteadt
Journal:  Phys Rev Lett       Date:  2003-07-03       Impact factor: 9.161

2.  A transcriptional signature of hub connectivity in the mouse connectome.

Authors:  Ben D Fulcher; Alex Fornito
Journal:  Proc Natl Acad Sci U S A       Date:  2016-01-15       Impact factor: 11.205

3.  Weak pairwise correlations imply strongly correlated network states in a neural population.

Authors:  Elad Schneidman; Michael J Berry; Ronen Segev; William Bialek
Journal:  Nature       Date:  2006-04-09       Impact factor: 49.962

Review 4.  Network hubs in the human brain.

Authors:  Martijn P van den Heuvel; Olaf Sporns
Journal:  Trends Cogn Sci       Date:  2013-12       Impact factor: 20.229

5.  GABAergic hub neurons orchestrate synchrony in developing hippocampal networks.

Authors:  P Bonifazi; M Goldin; M A Picardo; I Jorquera; A Cattani; G Bianconi; A Represa; Y Ben-Ari; R Cossart
Journal:  Science       Date:  2009-12-04       Impact factor: 47.728

6.  Collective dynamics of 'small-world' networks.

Authors:  D J Watts; S H Strogatz
Journal:  Nature       Date:  1998-06-04       Impact factor: 49.962

Review 7.  The log-dynamic brain: how skewed distributions affect network operations.

Authors:  György Buzsáki; Kenji Mizuseki
Journal:  Nat Rev Neurosci       Date:  2014-02-26       Impact factor: 34.870

8.  Rich cell-type-specific network topology in neocortical microcircuitry.

Authors:  Eyal Gal; Michael London; Amir Globerson; Srikanth Ramaswamy; Michael W Reimann; Eilif Muller; Henry Markram; Idan Segev
Journal:  Nat Neurosci       Date:  2017-06-05       Impact factor: 24.884

9.  Basin of attraction determines hysteresis in explosive synchronization.

Authors:  Yong Zou; Tiago Pereira; Michael Small; Zonghua Liu; Jürgen Kurths
Journal:  Phys Rev Lett       Date:  2014-03-18       Impact factor: 9.161

10.  Highly nonrandom features of synaptic connectivity in local cortical circuits.

Authors:  Sen Song; Per Jesper Sjöström; Markus Reigl; Sacha Nelson; Dmitri B Chklovskii
Journal:  PLoS Biol       Date:  2005-03-01       Impact factor: 8.029

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  2 in total

1.  Emergent hypernetworks in weakly coupled oscillators.

Authors:  Eddie Nijholt; Jorge Luis Ocampo-Espindola; Deniz Eroglu; István Z Kiss; Tiago Pereira
Journal:  Nat Commun       Date:  2022-08-17       Impact factor: 17.694

2.  Noise-induced network bursts and coherence in a calcium-mediated neural network.

Authors:  Na Yu; Gurpreet Jagdev; Michelle Morgovsky
Journal:  Heliyon       Date:  2021-12-20
  2 in total

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