ModelDB: Rat phrenic motor neuron (Amini et al 2004)

Rat phrenic motor neuron (Amini et al 2004)

Accession: 53572

We have developed a model for the rat phrenic motor neuron (PMN) that robustly replicates many experimentally observed behaviors of PMNs in response to pharmacological, ionic, and electrical perturbations using a single set of parameters.
Reference: Amini B, Bidani A, Zwischenberger JB, Clark JW (2004) A model of the rat phrenic motor neuron. IEEE Trans Biomed Eng 51:1103-14 [PubMed]

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Model Information (Click on a link to find other models with that property)

Model Type:	Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):	I Na,p; I Na,t; I L high threshold; I N; I T low threshold; I K,Ca;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:	C or C++ program (web link to model);
Model Concept(s):	Ion Channel Kinetics; Action Potentials; Spike Frequency Adaptation;
Implementer(s):

Search NeuronDB for information about: I K,Ca; I L high threshold; I N; I Na,p; I Na,t; I T low threshold;

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phrenic motor neuron model - clark lab

A MODEL OF THE RAT PHRENIC MOTOR NEURON
B. Amini¹ , A. Bidani², J.B. Zwischenberger³, J.W. Clark, Jr.⁴

¹Department of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, Houston, TX, USA
²Department of Internal Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
³Department of Surgery, University of Texas Medical Branch, Galveston, TX, USA
⁴Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA

Abstract
We have developed a model for the rat phrenic motor neuron (PMN) that robustly replicates many experimentally observed behaviors of PMNs in response to pharmacological, ionic, and electrical perturbations using a single set of parameters. Our model suggests that the after-depolarization (ADP) response seen in action potentials is a result of the slow deactivation of the fast sodium channel in the range of the ADP coupled with the activation of the L-type calcium channel (I_CaL). This current and its interactions with the small and large conductance calcium-activated potassium currents (I_KCaSK and I_KCaBK, respectively) is also important in the generation of spike frequency adaptation in the repetitive firing mode of activity. Other aspects of the model conform very well to experimental observations in both the action potential and repetitive firing mode of activity, including the role of I_KCaSK in the medium after-hyperpolarization (AHP), and the role of I_KCaBK in the fast AHP. We have made a number of predictions using the model, including the existence of two putative sodium currents (fast and persistent), as well as, functional roles for the N- and T-type calcium currents.

Computational Aspects
Simulations were performed on PCs running Linux and Windows XP and solved using a 5^th order Runge-Kutta-Merson numerical integration algorithm that includes an automatic step-size adjustment based on error estimates. The tolerance for the integration was 0.5×10^-6.

The equations were coded in the C language and compiled using the GNU C-compiler and Microsoft Visual C++ (for Linux and Windows XP, respectively). The executable (AApmn.exe) looks for a parameter file (pmn_parsed.d) and an initial condition file (pmn_init_cond.d) in the same directory. The parameters in pmn_parsed.d are in the following order: simulation duration (ms), baseline injected current (nA, for adjusting resting membrane potential), stimulation current (nA), stimulation start time (ms), stimulation end time (ms), followed by the maximal conductances for I_Na, I_CaL, I_K, I_A, I_D, I_R, I_BNa, I_BCa, I_NaK, I_CaP, I_NaCa, I_KCaSK, I_KCaBK, and I_NaP.

The simulation output is written to a text file (pmn_result.dat). Each row of this file has time as the first column followed by membrane potential, intracellular calcium, I_Na, I_CaL, I_K, I_A, I_D, I_R, I_BNa, I_BCa, I_NaK, I_CaP, I_NaCa, I_KCaSK, I_KCaBK, I_NaP, and I_total. A Matlab (MathWorks, Natick, MA) M-file (ReadResults.m) reads the output file and assigns variable names to the coulmns.

Files to Download
The aforementioned files can be downloaded as a tar.gz archive, pmn.tar.gz (8 KB). A separate archive, pmnMS.zip (46 KB), is presented for the convenience of Microsoft Visual C++ users. Microsoft windows users without access to Visual C++ can run the executable (AApmn.exe) found in the Release directory (see below). This directory also contains the initial condition and parameter files needed by the program.

The archive contents are shown below.

pmn.tar.gz

pmn

makefile

pmn_current.c

pmn_deriv.c

pmn_driver.c

pmn_reader.c

pmn_runge_kutta.c

pmn_subs.h

pmn_init_cond.d

pmn_parsed.d

ReadResults.m

pmnMS.zip

pmnMS

Release

AApmn.exe

pmn_init_cond.d

pmn_parsed.d

ReadResults.m

AApmn.dsp

AApmn.dsw

AApmn.ncb

AApmn.opt

AApmn.plg

pmn_current.c

pmn_deriv.c

pmn_driver.c

pmn_reader.c

pmn_runge_kutta.c

pmn_subs.h

Last modified August 16th, 2003 by Behrang Amini.
Please feel free to contact me at mailto:zyryab@rice.edu?subject=PMN Model Web Page with any questions regarding these files.

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