Literature DB >> 20702710

The membrane potential waveform of bursting pacemaker neurons is a predictor of their preferred frequency and the network cycle frequency.

Hua-an Tseng1, Farzan Nadim.   

Abstract

Many oscillatory networks involve neurons that exhibit intrinsic rhythmicity but possess a large variety of voltage-gated currents that interact in a complex fashion, making it difficult to determine which factors control frequency. Yet these neurons often have preferred (resonance) frequencies that can be close to the network frequency. Because the preferred frequency results from the dynamics of ionic currents, it can be assumed to depend on parameters that determine the neuron's oscillatory waveform shape. The pyloric network frequency in the crab Cancer borealis is correlated with the preferred frequency of its bursting pacemaker neurons anterior burster and pyloric dilator (PD). We measured the preferred frequency of the PD neuron in voltage clamp, which allows control of the oscillation voltage range and waveforms (sine waves and realistic oscillation waveforms), and showed that (1) the preferred frequency depends on the voltage range of the oscillating voltage waveform; (2) the slope of the waveform near its peak has a strongly negative correlation with the preferred frequency; and (3) correlations between parameters of the PD neuron oscillation waveform and its preferred frequency can be used to predict shifts in the network frequency. As predicted by these results, dynamic clamp shifts of the upper or lower voltage limits of the PD neuron waveform during ongoing oscillations changed the network frequency, consistent with the predictions from the preferred frequency. These results show that the voltage waveform of oscillatory neurons can be predictive of their preferred frequency and thus the network oscillation frequency.

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Year:  2010        PMID: 20702710      PMCID: PMC2944831          DOI: 10.1523/JNEUROSCI.1818-10.2010

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


  37 in total

1.  Theta-frequency bursting and resonance in cerebellar granule cells: experimental evidence and modeling of a slow k+-dependent mechanism.

Authors:  E D'Angelo; T Nieus; A Maffei; S Armano; P Rossi; V Taglietti; A Fontana; G Naldi
Journal:  J Neurosci       Date:  2001-02-01       Impact factor: 6.167

2.  Synaptic depression creates a switch that controls the frequency of an oscillatory circuit.

Authors:  F Nadim; Y Manor; N Kopell; E Marder
Journal:  Proc Natl Acad Sci U S A       Date:  1999-07-06       Impact factor: 11.205

Review 3.  Resonance, oscillation and the intrinsic frequency preferences of neurons.

Authors:  B Hutcheon; Y Yarom
Journal:  Trends Neurosci       Date:  2000-05       Impact factor: 13.837

4.  Computational model of electrically coupled, intrinsically distinct pacemaker neurons.

Authors:  Cristina Soto-Treviño; Pascale Rabbah; Eve Marder; Farzan Nadim
Journal:  J Neurophysiol       Date:  2005-02-23       Impact factor: 2.714

5.  Differential modulation of neural network and pacemaker activity underlying eupnea and sigh-breathing activities.

Authors:  Andrew K Tryba; Fernando Peña; Steven P Lieske; Jean-Charles Viemari; Muriel Thoby-Brisson; Jan-Marino Ramirez
Journal:  J Neurophysiol       Date:  2008-02-20       Impact factor: 2.714

6.  Electrically coupled pacemaker neurons respond differently to same physiological inputs and neurotransmitters.

Authors:  E Marder; J S Eisen
Journal:  J Neurophysiol       Date:  1984-06       Impact factor: 2.714

7.  Dynamic interaction of oscillatory neurons coupled with reciprocally inhibitory synapses acts to stabilize the rhythm period.

Authors:  Akira Mamiya; Farzan Nadim
Journal:  J Neurosci       Date:  2004-06-02       Impact factor: 6.167

Review 8.  Distributed effects of dopamine modulation in the crustacean pyloric network.

Authors:  R M Harris-Warrick; B R Johnson; J H Peck; P Kloppenburg; A Ayali; J Skarbinski
Journal:  Ann N Y Acad Sci       Date:  1998-11-16       Impact factor: 5.691

9.  Overexpression of a hyperpolarization-activated cation current (Ih) channel gene modifies the firing activity of identified motor neurons in a small neural network.

Authors:  Ying Zhang; Ricardo Oliva; Günter Gisselmann; Hanns Hatt; John Guckenheimer; Ronald M Harris-Warrick
Journal:  J Neurosci       Date:  2003-10-08       Impact factor: 6.167

10.  Subthreshold oscillations and resonant frequency in guinea-pig cortical neurons: physiology and modelling.

Authors:  Y Gutfreund; Y yarom; I Segev
Journal:  J Physiol       Date:  1995-03-15       Impact factor: 5.182

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  19 in total

1.  Peptide neuromodulation of synaptic dynamics in an oscillatory network.

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2.  Subthreshold amplitude and phase resonance in models of quadratic type: nonlinear effects generated by the interplay of resonant and amplifying currents.

Authors:  Horacio G Rotstein
Journal:  J Comput Neurosci       Date:  2015-01-15       Impact factor: 1.621

3.  Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.

Authors:  Andrea Bel; Horacio G Rotstein
Journal:  J Comput Neurosci       Date:  2019-03-20       Impact factor: 1.621

4.  Resonance modulation, annihilation and generation of anti-resonance and anti-phasonance in 3D neuronal systems: interplay of resonant and amplifying currents with slow dynamics.

Authors:  Horacio G Rotstein
Journal:  J Comput Neurosci       Date:  2017-05-31       Impact factor: 1.621

5.  Distinct Co-Modulation Rules of Synapses and Voltage-Gated Currents Coordinate Interactions of Multiple Neuromodulators.

Authors:  Xinping Li; Dirk Bucher; Farzan Nadim
Journal:  J Neurosci       Date:  2018-08-20       Impact factor: 6.167

6.  Postnatal development of electrophysiological properties of principal neurons in the rat basolateral amygdala.

Authors:  D E Ehrlich; S J Ryan; D G Rainnie
Journal:  J Physiol       Date:  2012-07-30       Impact factor: 5.182

7.  The frequency preference of neurons and synapses in a recurrent oscillatory network.

Authors:  Hua-an Tseng; Diana Martinez; Farzan Nadim
Journal:  J Neurosci       Date:  2014-09-17       Impact factor: 6.167

8.  Membrane potential resonance frequency directly influences network frequency through electrical coupling.

Authors:  Yinbo Chen; Xinping Li; Horacio G Rotstein; Farzan Nadim
Journal:  J Neurophysiol       Date:  2016-07-06       Impact factor: 2.714

9.  Spiking resonances in models with the same slow resonant and fast amplifying currents but different subthreshold dynamic properties.

Authors:  Horacio G Rotstein
Journal:  J Comput Neurosci       Date:  2017-10-24       Impact factor: 1.621

10.  The ionic mechanism of membrane potential oscillations and membrane resonance in striatal LTS interneurons.

Authors:  S C Song; J A Beatty; C J Wilson
Journal:  J Neurophysiol       Date:  2016-07-20       Impact factor: 2.714

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