Literature DB >> 20592116

Generation and preservation of the slow underlying membrane potential oscillation in model bursting neurons.

Clarence C Franklin1, John M Ball, David J Schulz, Satish S Nair.   

Abstract

The underlying membrane potential oscillation of both forced and endogenous slow-wave bursting cells affects the number of spikes per burst, which in turn affects outputs downstream. We use a biophysical model of a class of slow-wave bursting cells with six active currents to investigate and generalize correlations among maximal current conductances that might generate and preserve its underlying oscillation. We propose three phases for the underlying oscillation for this class of cells: generation, maintenance, and termination and suggest that different current modules coregulate to preserve the characteristics of each phase. Coregulation of I(Burst) and I(A) currents within distinct boundaries maintains the dynamics during the generation phase. Similarly, coregulation of I(CaT) and I(Kd) maintains the peak and duration of the underlying oscillation, whereas the calcium-activated I(KCa) ensures appropriate termination of the oscillation and adjusts the duration independent of peak.

Mesh:

Year:  2010        PMID: 20592116     DOI: 10.1152/jn.00444.2010

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  5 in total

1.  Neuromodulation independently determines correlated channel expression and conductance levels in motor neurons of the stomatogastric ganglion.

Authors:  Simone Temporal; Mohati Desai; Olga Khorkova; Gladis Varghese; Aihua Dai; David J Schulz; Jorge Golowasch
Journal:  J Neurophysiol       Date:  2011-10-12       Impact factor: 2.714

2.  Rapid homeostatic plasticity of intrinsic excitability in a central pattern generator network stabilizes functional neural network output.

Authors:  Joseph L Ransdell; Satish S Nair; David J Schulz
Journal:  J Neurosci       Date:  2012-07-11       Impact factor: 6.167

3.  Animal-to-animal variability in the phasing of the crustacean cardiac motor pattern: an experimental and computational analysis.

Authors:  Alex H Williams; Molly A Kwiatkowski; Adam L Mortimer; Eve Marder; Mary Lou Zeeman; Patsy S Dickinson
Journal:  J Neurophysiol       Date:  2013-02-27       Impact factor: 2.714

4.  Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment.

Authors:  Ted Brookings; Marie L Goeritz; Eve Marder
Journal:  J Neurophysiol       Date:  2014-07-09       Impact factor: 2.714

5.  Distinct current modules shape cellular dynamics in model neurons.

Authors:  Adel Alturki; Feng Feng; Ajay Nair; Vinay Guntu; Satish S Nair
Journal:  Neuroscience       Date:  2016-08-13       Impact factor: 3.590

  5 in total

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