Literature DB >> 21132359

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

Myongkeun Oh1, Victor Matveev.   

Abstract

Phase response is a powerful concept in the analysis of both weakly and non-weakly perturbed oscillators such as regularly spiking neurons, and is applicable if the oscillator returns to its limit cycle trajectory between successive perturbations. When the latter condition is violated, a formal application of the phase return map may yield phase values outside of its definition domain; in particular, strong synaptic inhibition may result in negative values of phase. The effect of a second perturbation arriving close to the first one is undetermined in this case. However, here we show that for a Morris-Lecar model of a spiking cell with strong time scale separation, extending the phase response function definition domain to an additional negative value branch allows to retain the accuracy of the phase response approach in the face of such strong inhibitory coupling. We use the resulting extended phase response function to accurately describe the response of a Morris-Lecar oscillator to consecutive non-weak synaptic inputs. This method is particularly useful when analyzing the dynamics of three or more non-weakly coupled cells, whereby more than one synaptic perturbation arrives per oscillation cycle into each cell. The method of perturbation prediction based on the negative-phase extension of the phase response function may be applicable to other excitable cell models characterized by slow voltage dynamics at hyperpolarized potentials.

Mesh:

Year:  2010        PMID: 21132359     DOI: 10.1007/s10827-010-0292-x

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  22 in total

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Authors:  P E Latham; B J Richmond; P G Nelson; S Nirenberg
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2.  Synchronization of strongly coupled excitatory neurons: relating network behavior to biophysics.

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3.  Electrical synapses and synchrony: the role of intrinsic currents.

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Journal:  J Neurosci       Date:  2003-07-16       Impact factor: 6.167

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Journal:  J Neurophysiol       Date:  2004-11-03       Impact factor: 2.714

5.  Loss of phase-locking in non-weakly coupled inhibitory networks of type-I model neurons.

Authors:  Myongkeun Oh; Victor Matveev
Journal:  J Comput Neurosci       Date:  2008-08-09       Impact factor: 1.621

6.  Phase resetting curves allow for simple and accurate prediction of robust N:1 phase locking for strongly coupled neural oscillators.

Authors:  Carmen C Canavier; Fatma Gurel Kazanci; Astrid A Prinz
Journal:  Biophys J       Date:  2009-07-08       Impact factor: 4.033

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Authors:  X J Wang; G Buzsáki
Journal:  J Neurosci       Date:  1996-10-15       Impact factor: 6.167

8.  Phase response characteristics of model neurons determine which patterns are expressed in a ring circuit model of gait generation.

Authors:  C C Canavier; R J Butera; R O Dror; D A Baxter; J W Clark; J H Byrne
Journal:  Biol Cybern       Date:  1997-12       Impact factor: 2.086

9.  Synchrony in excitatory neural networks.

Authors:  D Hansel; G Mato; C Meunier
Journal:  Neural Comput       Date:  1995-03       Impact factor: 2.026

10.  Isochrons and phaseless sets.

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

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  1 in total

1.  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

  1 in total

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