Literature DB >> 15190116

Using a hybrid neural system to reveal regulation of neuronal network activity by an intrinsic current.

Michael Sorensen1, Stephen DeWeerth, Gennady Cymbalyuk, Ronald L Calabrese.   

Abstract

The generation of rhythmic patterns by neuronal networks is a complex phenomenon, relying on the interaction of numerous intrinsic and synaptic currents, as well as modulatory agents. To investigate the functional contribution of an individual ionic current to rhythmic pattern generation in a network, we constructed a hybrid system composed of a silicon model neuron and a heart interneuron from the heartbeat timing network of the medicinal leech. When the model neuron and a heart interneuron are connected by inhibitory synapses, they produce rhythmic activity similar to that observed in the heartbeat network. We focused our studies on investigating the functional role of the hyperpolarization-activated inward current (I(h)) on the rhythmic bursts produced by the network. By introducing changes in both the model and the heart interneuron, we showed that I(h) determines both the period of rhythmic bursts and the balance of activity between the two sides of the network, because the amount and the activation/deactivation time constant of I(h) determines the length of time that a neuron spends in the inhibited phase of its burst cycle. Moreover, we demonstrated that the model neuron is an effective replacement for a heart interneuron and that changes made in the model can accurately mimic similar changes made in the living system. Finally, we used a previously developed mathematical model (Hill et al. 2001) of two mutually inhibitory interneurons to corroborate these findings. Our results demonstrated that this hybrid system technique is advantageous for investigating neuronal properties that are inaccessible with traditional techniques.

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Year:  2004        PMID: 15190116      PMCID: PMC6729308          DOI: 10.1523/JNEUROSCI.4449-03.2004

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  25 in total

1.  Inferring and quantifying the role of an intrinsic current in a mechanism for a half-center bursting oscillation: A dominant scale and hybrid dynamical systems analysis.

Authors:  Robert Clewley
Journal:  J Biol Phys       Date:  2011-03-17       Impact factor: 1.365

2.  A positive feedback at the cellular level promotes robustness and modulation at the circuit level.

Authors:  Julie Dethier; Guillaume Drion; Alessio Franci; Rodolphe Sepulchre
Journal:  J Neurophysiol       Date:  2015-08-26       Impact factor: 2.714

3.  Endogenous and half-center bursting in morphologically inspired models of leech heart interneurons.

Authors:  Anne-Elise Tobin; Ronald L Calabrese
Journal:  J Neurophysiol       Date:  2006-06-07       Impact factor: 2.714

4.  Myomodulin increases Ih and inhibits the NA/K pump to modulate bursting in leech heart interneurons.

Authors:  Anne-Elise Tobin; Ronald L Calabrese
Journal:  J Neurophysiol       Date:  2005-08-10       Impact factor: 2.714

5.  Transistor analogs of emergent iono-neuronal dynamics.

Authors:  Guy Rachmuth; Chi-Sang Poon
Journal:  HFSP J       Date:  2008-04-18

6.  Na(+)/K(+) pump interacts with the h-current to control bursting activity in central pattern generator neurons of leeches.

Authors:  Daniel Kueh; William H Barnett; Gennady S Cymbalyuk; Ronald L Calabrese
Journal:  Elife       Date:  2016-09-02       Impact factor: 8.140

Review 7.  The neural control of heartbeat in invertebrates.

Authors:  Ronald L Calabrese; Brian J Norris; Angela Wenning
Journal:  Curr Opin Neurobiol       Date:  2016-08-31       Impact factor: 6.627

8.  Control of transitions between locomotor-like and paw shake-like rhythms in a model of a multistable central pattern generator.

Authors:  Jessica Parker; Brian Bondy; Boris I Prilutsky; Gennady Cymbalyuk
Journal:  J Neurophysiol       Date:  2018-05-16       Impact factor: 2.714

9.  Geometry and dynamics of activity-dependent homeostatic regulation in neurons.

Authors:  Andrey V Olypher; Astrid A Prinz
Journal:  J Comput Neurosci       Date:  2010-02-09       Impact factor: 1.621

10.  Patterns of presynaptic activity and synaptic strength interact to produce motor output.

Authors:  Terrence Michael Wright; Ronald L Calabrese
Journal:  J Neurosci       Date:  2011-11-30       Impact factor: 6.167

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