Transition to reconstructibility in weakly coupled networks

Across scientific disciplines, thresholded pairwise measures of statistical dependence between time series are taken as proxies for the interactions between the dynamical units of a network. Yet such correlation measures often fail to reflect the underlying physical interactions accurately. Here we...

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Bibliographic Details
Published in:PloS one 2017-10, Vol.12 (10), p.e0186624
Main Authors: Lünsmann, Benedict J, Kirst, Christoph, Timme, Marc
Format: Article
Language:English
Subjects:
Algorithms
Biology and Life Sciences
Computer and Information Sciences
Computer Simulation
Connectivity
Correlation
Correlation analysis
Dynamical systems
Models, Neurological
Neural networks
Neurosciences
Noise
Nonlinear Dynamics
Physical Sciences
Physics
Research and Analysis Methods
Time series
Transportation networks
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Summary:Across scientific disciplines, thresholded pairwise measures of statistical dependence between time series are taken as proxies for the interactions between the dynamical units of a network. Yet such correlation measures often fail to reflect the underlying physical interactions accurately. Here we systematically study the problem of reconstructing direct physical interaction networks from thresholding correlations. We explicate how local common cause and relay structures, heterogeneous in-degrees and non-local structural properties of the network generally hinder reconstructibility. However, in the limit of weak coupling strengths we prove that stationary systems with dynamics close to a given operating point transition to universal reconstructiblity across all network topologies.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0186624