Evidence map›Paper›PMID 31656136›Full record

ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2019

State-dependent effective interactions in oscillator networks through coupling functions with dead zones.

Peter Ashwin, Christian Bick, Camille Poignard

Abstract read
In one paragraph

Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2019
    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

3 authors.

Peter AshwinEPSRC Centre for Predictive Modelling in Healthcare and Centre for Systems, Dynamics & Control, Department of Mathematics, University of Exeter, Exeter, Devon, UK.
Christian BickEPSRC Centre for Predictive Modelling in Healthcare and Centre for Systems, Dynamics & Control, Department of Mathematics, University of Exeter, Exeter, Devon, UK.
Camille PoignardEPSRC Centre for Predictive Modelling in Healthcare and Centre for Systems, Dynamics & Control, Department of Mathematics, University of Exeter, Exeter, Devon, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dynamics of networks of interacting dynamical systems depend on the nature of the coupling between individual units. We explore networks of oscillatory units with coupling functions that have 'dead zones', that is the coupling functions are zero on sets with interior. For such networks, it is convenient to look at the effective interactions between units rather than the (fixed) structural connectivity to understand the network dynamics. For example, oscillators may effectively decouple in particular phase configurations. Along trajectories, the effective interactions are not necessarily static, but the effective coupling may evolve in time. Here, we formalize the concepts of dead zones and effective interactions. We elucidate how the coupling function shapes the possible effective interaction schemes and how they evolve in time. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.

Indexed as

Models, TheoreticalComputer Graphicscoupled oscillatorcoupling functionnetwork dynamical system

Identifiers

PMID31656136
PMCPMC6833998

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.