Literature DB >> 19580744

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

Carmen C Canavier1, Fatma Gurel Kazanci, Astrid A Prinz.   

Abstract

Existence and stability criteria for harmonic locking modes were derived for two reciprocally pulse coupled oscillators based on their first and second order phase resetting curves. Our theoretical methods are general in the sense that no assumptions about the strength of coupling, type of synaptic coupling, and model are made. These methods were then tested using two reciprocally inhibitory Wang and Buzsáki model neurons. The existence of bands of 2:1, 3:1, 4:1, and 5:1 phase locking in the relative frequency parameter space was predicted correctly, as was the phase of the slow neuron's spike within the cycle of the fast neuron in which it occurred. For weak coupling the bands are very narrow, but strong coupling broadens the bands. The predictions of the pulse coupled method agreed with weak coupling methods in the weak coupling regime, but extended predictability into the strong coupling regime. We show that our prediction method generalizes to pairs of neural oscillators coupled through excitatory synapses, and to networks of multiple oscillatory neurons. The main limitation of the method is the central assumption that the effect of each input dies out before the next input is received.

Mesh:

Year:  2009        PMID: 19580744      PMCID: PMC2711386          DOI: 10.1016/j.bpj.2009.04.016

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  36 in total

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2.  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

3.  Using heterogeneity to predict inhibitory network model characteristics.

Authors:  F K Skinner; J Y J Chung; I Ncube; P A Murray; S A Campbell
Journal:  J Neurophysiol       Date:  2004-11-17       Impact factor: 2.714

4.  On the formation of gamma-coherent cell assemblies by oriens lacunosum-moleculare interneurons in the hippocampus.

Authors:  Adriano B L Tort; Horacio G Rotstein; Tamar Dugladze; Tengis Gloveli; Nancy J Kopell
Journal:  Proc Natl Acad Sci U S A       Date:  2007-08-06       Impact factor: 11.205

5.  Predictions of phase-locking in excitatory hybrid networks: excitation does not promote phase-locking in pattern-generating networks as reliably as inhibition.

Authors:  Fred H Sieling; Carmen C Canavier; Astrid A Prinz
Journal:  J Neurophysiol       Date:  2009-04-08       Impact factor: 2.714

6.  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

7.  Prediction of entrainment and 1:1 phase-locked modes in two-neuron networks based on the phase resetting curve method.

Authors:  Sorinel Adrian Oprisan; Christian Boutan
Journal:  Int J Neurosci       Date:  2008-06       Impact factor: 2.292

8.  Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model.

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

9.  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

Review 10.  Application of the mathematics of coupled oscillator systems to the analysis of the neural control of locomotion.

Authors:  P S Stein
Journal:  Fed Proc       Date:  1977-06
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  13 in total

1.  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

2.  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

3.  Predictions of phase-locking in excitatory hybrid networks: excitation does not promote phase-locking in pattern-generating networks as reliably as inhibition.

Authors:  Fred H Sieling; Carmen C Canavier; Astrid A Prinz
Journal:  J Neurophysiol       Date:  2009-04-08       Impact factor: 2.714

Review 4.  Variability, compensation, and modulation in neurons and circuits.

Authors:  Eve Marder
Journal:  Proc Natl Acad Sci U S A       Date:  2011-03-07       Impact factor: 11.205

5.  On cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus.

Authors:  Robson Scheffer-Teixeira; Adriano Bl Tort
Journal:  Elife       Date:  2016-12-07       Impact factor: 8.140

6.  Inhibitory feedback promotes stability in an oscillatory network.

Authors:  F Nadim; S Zhao; L Zhou; A Bose
Journal:  J Neural Eng       Date:  2011-11-04       Impact factor: 5.379

Review 7.  Pulse coupled oscillators and the phase resetting curve.

Authors:  Carmen C Canavier; Srisairam Achuthan
Journal:  Math Biosci       Date:  2010-05-10       Impact factor: 2.144

8.  Short conduction delays cause inhibition rather than excitation to favor synchrony in hybrid neuronal networks of the entorhinal cortex.

Authors:  Shuoguo Wang; Lakshmi Chandrasekaran; Fernando R Fernandez; John A White; Carmen C Canavier
Journal:  PLoS Comput Biol       Date:  2012-01-05       Impact factor: 4.475

9.  Cross-frequency and iso-frequency estimation of functional corticomuscular coupling after stroke.

Authors:  Ping Xie; Xiaohui Pang; Shengcui Cheng; Yuanyuan Zhang; Yinan Yang; Xiaoli Li; Xiaoling Chen
Journal:  Cogn Neurodyn       Date:  2020-09-16       Impact factor: 3.473

10.  Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks.

Authors:  Umeshkanta S Thounaojam; Jianxia Cui; Sharon E Norman; Robert J Butera; Carmen C Canavier
Journal:  PLoS Comput Biol       Date:  2014-05-15       Impact factor: 4.475

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