Literature DB >> 17930210

Correlations, fluctuations, and stability of a finite-size network of coupled oscillators.

Michael A Buice1, Carson C Chow.   

Abstract

The incoherent state of the Kuramoto model of coupled oscillators exhibits marginal modes in mean field theory. We demonstrate that corrections due to finite size effects render these modes stable in the subcritical case, i.e., when the population is not synchronous. This demonstration is facilitated by the construction of a nonequilibrium statistical field theoretic formulation of a generic model of coupled oscillators. This theory is consistent with previous results. In the all-to-all case, the fluctuations in this theory are due completely to finite size corrections, which can be calculated in an expansion in 1/N, where N is the number of oscillators. The N-->infinity limit of this theory is what is traditionally called mean field theory for the Kuramoto model.

Mesh:

Year:  2007        PMID: 17930210     DOI: 10.1103/PhysRevE.76.031118

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  16 in total

1.  A coarse-grained framework for spiking neuronal networks: between homogeneity and synchrony.

Authors:  Jiwei Zhang; Douglas Zhou; David Cai; Aaditya V Rangan
Journal:  J Comput Neurosci       Date:  2013-12-13       Impact factor: 1.621

2.  A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.

Authors:  J W Zhang; A V Rangan
Journal:  J Comput Neurosci       Date:  2015-01-21       Impact factor: 1.621

3.  A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs.

Authors:  Jiwei Zhang; Yuxiu Shao; Aaditya V Rangan; Louis Tao
Journal:  J Comput Neurosci       Date:  2019-02-16       Impact factor: 1.621

4.  Beyond mean field theory: statistical field theory for neural networks.

Authors:  Michael A Buice; Carson C Chow
Journal:  J Stat Mech       Date:  2013-03       Impact factor: 2.231

5.  Before and beyond the Wilson-Cowan equations.

Authors:  Carson C Chow; Yahya Karimipanah
Journal:  J Neurophysiol       Date:  2020-03-18       Impact factor: 2.714

6.  Effective stochastic behavior in dynamical systems with incomplete information.

Authors:  Michael A Buice; Carson C Chow
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2011-11-17

7.  Finite-size effects for spiking neural networks with spatially dependent coupling.

Authors:  Si-Wei Qiu; Carson C Chow
Journal:  Phys Rev E       Date:  2018-12-27       Impact factor: 2.529

Review 8.  From the statistics of connectivity to the statistics of spike times in neuronal networks.

Authors:  Gabriel Koch Ocker; Yu Hu; Michael A Buice; Brent Doiron; Krešimir Josić; Robert Rosenbaum; Eric Shea-Brown
Journal:  Curr Opin Neurobiol       Date:  2017-08-30       Impact factor: 6.627

9.  Systematic fluctuation expansion for neural network activity equations.

Authors:  Michael A Buice; Jack D Cowan; Carson C Chow
Journal:  Neural Comput       Date:  2010-02       Impact factor: 2.026

10.  Balance between noise and adaptation in competition models of perceptual bistability.

Authors:  Asya Shpiro; Ruben Moreno-Bote; Nava Rubin; John Rinzel
Journal:  J Comput Neurosci       Date:  2009-01-06       Impact factor: 1.621

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