Literature DB >> 11205354

Dynamics of two electrically coupled chaotic neurons: experimental observations and model analysis.

P Varona1, J J Torres, H D Abarbanel, M I Rabinovich, R C Elson.   

Abstract

Conductance-based models of neurons from the lobster stomatogastric ganglion (STG) have been developed to understand the observed chaotic behavior of individual STG neurons. These models identify an additional slow dynamical process calcium exchange and storage in the endoplasmic reticulum as a biologically plausible source for the observed chaos in the oscillations of these cells. In this paper we test these ideas further by exploring the dynamical behavior when two model neurons are coupled by electrical or gap junction connections. We compare in detail the model results to the laboratory measurements of electrically-coupled neurons that we reported earlier. The experiments on the biological neurons varied the strength of the effective coupling by applying a parallel, artificial synapse, which changed both the magnitude and polar-of the conductance between the neurons. We observed a sequence of bifarctions that took the neurons from strongly synchronized in-phase behavior. through uncorrelated chaotic oscillations to strongly synchronized and now regular out-of-phase behavior. The model calculations reproduce these observations quantitatively, indicating that slow subcellular processes could account for the mechanisms involved in the synchronization and regularization of the otherwise individual chaotic activities.

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Year:  2001        PMID: 11205354     DOI: 10.1007/s004220000198

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


  11 in total

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Journal:  Cogn Neurodyn       Date:  2018-09-11       Impact factor: 5.082

2.  Cluster burst synchronization in a scale-free network of inhibitory bursting neurons.

Authors:  Sang-Yoon Kim; Woochang Lim
Journal:  Cogn Neurodyn       Date:  2019-07-10       Impact factor: 5.082

3.  Spike width and frequency alter stability of phase-locking in electrically coupled neurons.

Authors:  Ramana Dodla; Charles J Wilson
Journal:  Biol Cybern       Date:  2013-04-17       Impact factor: 2.086

4.  Effect of spike-timing-dependent plasticity on stochastic burst synchronization in a scale-free neuronal network.

Authors:  Sang-Yoon Kim; Woochang Lim
Journal:  Cogn Neurodyn       Date:  2018-01-10       Impact factor: 5.082

Review 5.  Silicon central pattern generators for cardiac diseases.

Authors:  Alain Nogaret; Erin L O'Callaghan; Renata M Lataro; Helio C Salgado; C Daniel Meliza; Edward Duncan; Henry D I Abarbanel; Julian F R Paton
Journal:  J Physiol       Date:  2015-01-05       Impact factor: 5.182

6.  Generalization of the dynamic clamp concept in neurophysiology and behavior.

Authors:  Pablo Chamorro; Carlos Muñiz; Rafael Levi; David Arroyo; Francisco B Rodríguez; Pablo Varona
Journal:  PLoS One       Date:  2012-07-19       Impact factor: 3.240

7.  Implementing Signature Neural Networks with Spiking Neurons.

Authors:  José Luis Carrillo-Medina; Roberto Latorre
Journal:  Front Comput Neurosci       Date:  2016-12-20       Impact factor: 2.380

8.  Asymmetry Factors Shaping Regular and Irregular Bursting Rhythms in Central Pattern Generators.

Authors:  Irene Elices; Pablo Varona
Journal:  Front Comput Neurosci       Date:  2017-02-16       Impact factor: 2.380

9.  Probing the dynamics of identified neurons with a data-driven modeling approach.

Authors:  Thomas Nowotny; Rafael Levi; Allen I Selverston
Journal:  PLoS One       Date:  2008-07-09       Impact factor: 3.240

10.  A model-based prediction of the calcium responses in the striatal synaptic spines depending on the timing of cortical and dopaminergic inputs and post-synaptic spikes.

Authors:  Takashi Nakano; Junichiro Yoshimoto; Kenji Doya
Journal:  Front Comput Neurosci       Date:  2013-09-13       Impact factor: 2.380

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