Literature DB >> 19257636

Asynchronous response of coupled pacemaker neurons.

Ramana Dodla1, Charles J Wilson.   

Abstract

We study a network model of two conductance-based pacemaker neurons of differing natural frequency, coupled with either mutual excitation or inhibition, and receiving shared random inhibitory synaptic input. The networks may phase lock spike to spike for strong mutual coupling. But the shared input can desynchronize the locked spike pairs by selectively eliminating the lagging spike or modulating its timing with respect to the leading spike depending on their separation time window. Such loss of synchrony is also found in a large network of sparsely coupled heterogeneous spiking neurons receiving shared input.

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Year:  2009        PMID: 19257636      PMCID: PMC2679421          DOI: 10.1103/PhysRevLett.102.068102

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  25 in total

1.  The number of synaptic inputs and the synchrony of large, sparse neuronal networks.

Authors:  D Golomb; D Hansel
Journal:  Neural Comput       Date:  2000-05       Impact factor: 2.026

2.  Activity patterns in a model for the subthalamopallidal network of the basal ganglia.

Authors:  D Terman; J E Rubin; A C Yew; C J Wilson
Journal:  J Neurosci       Date:  2002-04-01       Impact factor: 6.167

3.  Dynamics of spiking neurons connected by both inhibitory and electrical coupling.

Authors:  Timothy J Lewis; John Rinzel
Journal:  J Comput Neurosci       Date:  2003 May-Jun       Impact factor: 1.621

4.  Synchrony of neuronal oscillations controlled by GABAergic reversal potentials.

Authors:  Ho Young Jeong; Boris Gutkin
Journal:  Neural Comput       Date:  2007-03       Impact factor: 2.026

5.  Synchronization of electrically coupled pairs of inhibitory interneurons in neocortex.

Authors:  Jaime G Mancilla; Timothy J Lewis; David J Pinto; John Rinzel; Barry W Connors
Journal:  J Neurosci       Date:  2007-02-21       Impact factor: 6.167

6.  Synchronization of excitatory neurons with strongly heterogeneous phase responses.

Authors:  Yasuhiro Tsubo; Jun-nosuke Teramae; Tomoki Fukai
Journal:  Phys Rev Lett       Date:  2007-11-26       Impact factor: 9.161

7.  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

8.  Detecting dynamical interdependence and generalized synchrony through mutual prediction in a neural ensemble.

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  1996-12

9.  Synchronization and oscillatory dynamics in heterogeneous, mutually inhibited neurons.

Authors:  J A White; C C Chow; J Ritt; C Soto-Treviño; N Kopell
Journal:  J Comput Neurosci       Date:  1998-03       Impact factor: 1.621

10.  Synchrony in excitatory neural networks.

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

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  1 in total

1.  Robustness, variability, phase dependence, and longevity of individual synaptic input effects on spike timing during fluctuating synaptic backgrounds: a modeling study of globus pallidus neuron phase response properties.

Authors:  N W Schultheiss; J R Edgerton; D Jaeger
Journal:  Neuroscience       Date:  2012-06-01       Impact factor: 3.590

  1 in total

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