Literature DB >> 1725879

Simulation of the bursting activity of neuron R15 in Aplysia: role of ionic currents, calcium balance, and modulatory transmitters.

C C Canavier1, J W Clark, J H Byrne.   

Abstract

1. An equivalent circuit model of the R15 bursting neuron in Aplysia has been combined with a fluid compartment model, resulting in a model that incorporates descriptions of most of the membrane ion channels that are known to exist in the somata of R15, as well as providing a Ca2+ balance on the cell. 2. A voltage-activated, calcium-inactivated Ca2+ current (denoted the slow inward current ISI) was sufficient to produce bursting activity without invoking any other calcium-dependent currents (such as a nonspecific cation current, INS, or a calcium-activated K+ current, IK,Ca). Furthermore, many characteristics of a typical R15 burst could be simulated, such as a parabolic variation in interspike interval, the depolarizing afterpotential (DAP), and the progressive decrease in the undershoots of spikes during a burst. 3. The dynamic activity of R15 was analyzed by separately characterizing two different temporal domains; the fast dynamics associated with action potentials and the slow dynamics associated with low-amplitude oscillations lasting tens of seconds ("slow waves"). The slow dynamics were isolated by setting the Na+ conductance (gNa) to zero and then studied by the use of a system of equations reduced to two variables: intracellular concentration of Ca2+ and membrane potential. The fixed point of the system was located at the intersection of the nullclines for these two variables. A stability analysis of the fixed point was then used to determine whether a given set of parameters would produce slow-wave activity. 4. If the reduced model predicted slow-wave oscillations for a given set of parameters with gNa set to zero, then bursting activity was observed for the same set of parameters in the full model with gNa reset to its control value. However, for certain sets of parameters with gNa at its usual value, the full model exhibited bursting activity because of a slow oscillation produced by the activation of INS by action potentials. This oscillation resulted from an interaction between the fast and slow dynamics that the reduced model alone could not predict and was not observed when gNa was subsequently set to zero. If gNS was also set to zero, this discrepancy disappeared.(ABSTRACT TRUNCATED AT 400 WORDS)

Entities:  

Mesh:

Substances:

Year:  1991        PMID: 1725879     DOI: 10.1152/jn.1991.66.6.2107

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


  29 in total

1.  Global structure, robustness, and modulation of neuronal models.

Authors:  M S Goldman; J Golowasch; E Marder; L F Abbott
Journal:  J Neurosci       Date:  2001-07-15       Impact factor: 6.167

2.  Studies of chemoreceptor perception in mollusks.

Authors:  N N Kamardin; Y Shalanki; K S Rozha; A D Nozdrachev
Journal:  Neurosci Behav Physiol       Date:  2001 Mar-Apr

3.  Dynamics from a time series: can we extract the phase resetting curve from a time series?

Authors:  S A Oprisan; V Thirumalai; C C Canavier
Journal:  Biophys J       Date:  2003-05       Impact factor: 4.033

4.  Mechanism, dynamics, and biological existence of multistability in a large class of bursting neurons.

Authors:  Jonathan P Newman; Robert J Butera
Journal:  Chaos       Date:  2010-06       Impact factor: 3.642

5.  Generation of very slow neuronal rhythms and chaos near the Hopf bifurcation in single neuron models.

Authors:  Shinji Doi; Sadatoshi Kumagai
Journal:  J Comput Neurosci       Date:  2005-12       Impact factor: 1.621

6.  Capturing the bursting dynamics of a two-cell inhibitory network using a one-dimensional map.

Authors:  Victor Matveev; Amitabha Bose; Farzan Nadim
Journal:  J Comput Neurosci       Date:  2007-04-18       Impact factor: 1.621

7.  Low dimensional model of bursting neurons.

Authors:  X Zhao; J W Kim; P A Robinson; C J Rennie
Journal:  J Comput Neurosci       Date:  2013-06-22       Impact factor: 1.621

8.  Modeling Hermissenda: I. Differential contributions of IA and IC to type-B cell plasticity.

Authors:  J W Fost; G A Clark
Journal:  J Comput Neurosci       Date:  1996-06       Impact factor: 1.621

9.  How neurons may compute: the case of insect sexual pheromone discrimination.

Authors:  C Linster; M Kerszberg; C Masson
Journal:  J Comput Neurosci       Date:  1994-08       Impact factor: 1.621

10.  Evidence for a novel bursting mechanism in rodent trigeminal neurons.

Authors:  C A Del Negro; C F Hsiao; S H Chandler; A Garfinkel
Journal:  Biophys J       Date:  1998-07       Impact factor: 4.033

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.