Literature DB >> 22290314

Limitations of perturbative techniques in the analysis of rhythms and oscillations.

Kevin K Lin1, Kyle C A Wedgwood, Stephen Coombes, Lai-Sang Young.   

Abstract

Perturbation theory is an important tool in the analysis of oscillators and their response to external stimuli. It is predicated on the assumption that the perturbations in question are “sufficiently weak”, an assumption that is not always valid when perturbative methods are applied. In this paper, we identify a number of concrete dynamical scenarios in which a standard perturbative technique, based on the infinitesimal phase response curve (PRC), is shown to give different predictions than the full model. Shear-induced chaos, i.e., chaotic behavior that results from the amplification of small perturbations by underlying shear, is missed entirely by the PRC. We show also that the presence of “sticky” phase–space structures tend to cause perturbative techniques to overestimate the frequencies and regularity of the oscillations. The phenomena we describe can all be observed in a simple 2D neuron model, which we choose for illustration as the PRC is widely used in mathematical neuroscience.

Mesh:

Year:  2013        PMID: 22290314     DOI: 10.1007/s00285-012-0506-0

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  7 in total

1.  Symmetry in locomotor central pattern generators and animal gaits.

Authors:  M Golubitsky; I Stewart; P L Buono; J J Collins
Journal:  Nature       Date:  1999-10-14       Impact factor: 49.962

2.  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

3.  On the phase reduction and response dynamics of neural oscillator populations.

Authors:  Eric Brown; Jeff Moehlis; Philip Holmes
Journal:  Neural Comput       Date:  2004-04       Impact factor: 2.026

4.  Beyond two-cell networks: experimental measurement of neuronal responses to multiple synaptic inputs.

Authors:  Theoden I Netoff; Corey D Acker; Jonathan C Bettencourt; John A White
Journal:  J Comput Neurosci       Date:  2005-06       Impact factor: 1.621

5.  Spike-time reliability of layered neural oscillator networks.

Authors:  Kevin K Lin; Eric Shea-Brown; Lai-Sang Young
Journal:  J Comput Neurosci       Date:  2009-01-21       Impact factor: 1.621

6.  Limit cycles in predator-prey communities.

Authors:  R M May
Journal:  Science       Date:  1972-09-08       Impact factor: 47.728

7.  Isochrons and phaseless sets.

Authors:  J Guckenheimer
Journal:  J Math Biol       Date:  2017-03-15       Impact factor: 2.259

  7 in total
  5 in total

1.  Mathematical Frameworks for Oscillatory Network Dynamics in Neuroscience.

Authors:  Peter Ashwin; Stephen Coombes; Rachel Nicks
Journal:  J Math Neurosci       Date:  2016-01-06       Impact factor: 1.300

2.  The Use of Reduced Models to Generate Irregular, Broad-Band Signals That Resemble Brain Rhythms.

Authors:  Benjamin Ambrosio; Lai-Sang Young
Journal:  Front Comput Neurosci       Date:  2022-06-13       Impact factor: 3.387

3.  Phase-amplitude response functions for transient-state stimuli.

Authors:  Oriol Castejón; Antoni Guillamon; Gemma Huguet
Journal:  J Math Neurosci       Date:  2013-08-14       Impact factor: 1.300

4.  Phase-amplitude descriptions of neural oscillator models.

Authors:  Kyle Ca Wedgwood; Kevin K Lin; Ruediger Thul; Stephen Coombes
Journal:  J Math Neurosci       Date:  2013-01-24       Impact factor: 1.300

5.  A computational study of spike time reliability in two types of threshold dynamics.

Authors:  Na Yu; Yue-Xian Li; Rachel Kuske
Journal:  J Math Neurosci       Date:  2013-08-14       Impact factor: 1.300

  5 in total

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