Evidence map›Paper›PMID 28764402›Full record

ArticleChaos (Woodbury, N.Y.)2017

Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators.

Lia Papadopoulos, Jason Z Kim, Jürgen Kurths, Danielle S Bassett

Abstract read
In one paragraph

Article in Chaos (Woodbury, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Functional control of oscillator networks.Nature communications · 2022
    Article
  9. Adaptive rewiring in nonuniform coupled oscillators.Network neuroscience (Cambridge, Mass.) · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. The road ahead in clinical network neuroscience.Network neuroscience (Cambridge, Mass.) · 2019
    Review
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lia PapadopoulosDepartment of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Jason Z KimDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Jürgen KurthsPotsdam Institute for Climate Impact Research - Telegraphenberg A 31, 14473 Potsdam, Germany.ORCID 0000000259264276
Danielle S BassettDepartment of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

Funding

Training in Structural, Physiologic and Functional MRIT32EB020087 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI JAMES C GEE, Chamith Sudesh Rajapakse · 2016 to 2026
$2.1M
NIBIB NIH HHS T32 EB020087
6 · The paper itself

Abstract

Synchronization of non-identical oscillators coupled through complex networks is an important example of collective behavior, and it is interesting to ask how the structural organization of network interactions influences this process. Several studies have explored and uncovered optimal topologies for synchronization by making purposeful alterations to a network. On the other hand, the connectivity patterns of many natural systems are often not static, but are rather modulated over time according to their dynamics. However, this co-evolution and the extent to which the dynamics of the individual units can shape the organization of the network itself are less well understood. Here, we study initially randomly connected but locally adaptive networks of Kuramoto oscillators. In particular, the system employs a co-evolutionary rewiring strategy that depends only on the instantaneous, pairwise phase differences of neighboring oscillators, and that conserves the total number of edges, allowing the effects of local reorganization to be isolated. We find that a simple rule-which preserves connections between more out-of-phase oscillators while rewiring connections between more in-phase oscillators-can cause initially disordered networks to organize into more structured topologies that support enhanced synchronization dynamics. We examine how this process unfolds over time, finding a dependence on the intrinsic frequencies of the oscillators, the global coupling, and the network density, in terms of how the adaptive mechanism reorganizes the network and influences the dynamics. Importantly, for large enough coupling and after sufficient adaptation, the resulting networks exhibit interesting characteristics, including degree-frequency and frequency-neighbor frequency correlations. These properties have previously been associated with optimal synchronization or explosive transitions in which the networks were constructed using global information. On the contrary, by considering a time-dependent interplay between structure and dynamics, this work offers a mechanism through which emergent phenomena and organization can arise in complex systems utilizing local rules.

Identifiers

PMID28764402
PMCPMC5552408

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.