Literature DB >> 20809292

A mathematical criterion based on phase response curves for stability in a ring of coupled oscillators.

R O Dror1, C C Canavier, R J Butera, J W Clark, J H Byrne.   

Abstract

Canavier et al. (1997) used phase response curves (PRCs) of individual oscillators to characterize the possible modes of phase-locked entrainment of an N-oscillator ring network. We extend this work by developing a mathematical criterion to determine the local stability of such a mode based on the PRCs. Our method does not assume symmetry; neither the oscillators nor their connections need be identical. To use these techniques for predicting modes and determining their stability, one need only determine the PRC of each oscillator in the ring either experimentally or from a computational model. We show that network stability cannot be determined by simply testing the ability of each oscillator to entrain the next. Stability depends on the number of neurons in the ring, the type of mode, and the slope of each PRC at the point of entrainment of the respective neuron. We also describe simple criteria which are either necessary or sufficient for stability and examine the implications of these results.

Year:  1999        PMID: 20809292     DOI: 10.1007/s004220050501

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  20 in total

1.  Dynamics from a time series: can we extract the phase resetting curve from a time series?

Authors:  S A Oprisan; V Thirumalai; C C Canavier
Journal:  Biophys J       Date:  2003-05       Impact factor: 4.033

2.  Phase resetting and phase locking in hybrid circuits of one model and one biological neuron.

Authors:  S A Oprisan; A A Prinz; C C Canavier
Journal:  Biophys J       Date:  2004-10       Impact factor: 4.033

3.  Phase resetting reduces theta-gamma rhythmic interaction to a one-dimensional map.

Authors:  Paola Malerba; Nancy Kopell
Journal:  J Math Biol       Date:  2012-04-21       Impact factor: 2.259

4.  Phase-response curves and synchronized neural networks.

Authors:  Roy M Smeal; G Bard Ermentrout; John A White
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-08-12       Impact factor: 6.237

5.  Non-weak inhibition and phase resetting at negative values of phase in cells with fast-slow dynamics at hyperpolarized potentials.

Authors:  Myongkeun Oh; Victor Matveev
Journal:  J Comput Neurosci       Date:  2010-12-04       Impact factor: 1.621

6.  Stability of two cluster solutions in pulse coupled networks of neural oscillators.

Authors:  Lakshmi Chandrasekaran; Srisairam Achuthan; Carmen C Canavier
Journal:  J Comput Neurosci       Date:  2010-08-20       Impact factor: 1.621

7.  Using phase resetting to predict 1:1 and 2:2 locking in two neuron networks in which firing order is not always preserved.

Authors:  Selva K Maran; Carmen C Canavier
Journal:  J Comput Neurosci       Date:  2007-06-19       Impact factor: 1.621

8.  Functional phase response curves: a method for understanding synchronization of adapting neurons.

Authors:  Jianxia Cui; Carmen C Canavier; Robert J Butera
Journal:  J Neurophysiol       Date:  2009-05-06       Impact factor: 2.714

9.  Phase response theory explains cluster formation in sparsely but strongly connected inhibitory neural networks and effects of jitter due to sparse connectivity.

Authors:  Ruben A Tikidji-Hamburyan; Conrad A Leonik; Carmen C Canavier
Journal:  J Neurophysiol       Date:  2019-02-06       Impact factor: 2.714

10.  Hippocampal CA1 pyramidal neurons exhibit type 1 phase-response curves and type 1 excitability.

Authors:  Shuoguo Wang; Maximilian M Musharoff; Carmen C Canavier; Sonia Gasparini
Journal:  J Neurophysiol       Date:  2013-03-06       Impact factor: 2.714

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