Model of AngII signaling and membrane electrophysiology (Makadia, Anderson, Fey et al., 2015)

 Download zip file 
Help downloading and running models
Accession:156830
We developed a novel multiscale model to bridge neuropeptide receptor-activated signaling pathway with membrane electrophysiology. The model studies the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. The multiscale model was implemented as a set of ordinary differential equations solved using the ode15s solver in Matlab (Mathworks, USA). The signaling reactions were modeled with either mass-action or Michaelis--Menten kinetics and ion channel electrophysiology was modeled according to the Hodgkin-Huxley formalism. These models were initially validated against their respective data domains independently and were integrated to develop a multiscale model of signaling and electrophysiology.
Reference:
1 . Makadia HK, Anderson WD, Fey D, Sauter T, Schwaber JS, Vadigepalli R (2015) Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology. Biophys J 108:211-23 [PubMed]
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: Brainstem;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Signaling pathways; Calcium dynamics; Neuromodulation; Multiscale;
Implementer(s): Makadia, Hirenkumar K [hiren.makadia at gmail.com]; Anderson, Warren D [warren.anderson at jefferson.edu]; Fey, Dirk [dirk.fey at ucd.ie]; Vadigepalli, Rajanikanth [Rajanikanth.Vadigepalli at jefferson.edu];
function [] = plot_firingrate()
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function to plot firing rate
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

tic 

clc
clear all

format long eng
options = odeset( 'RelTol', 1e-9, 'AbsTol', 1e-9 );

% initial time (negative value indicates the time for steady state)
ti = -100;
% time step (0.0005 s)
dt = 0.5*10^(-3);
% final time 
tf = 300; % 800 for step response
tspan = ti:dt:tf;

% load initial conditons
y0 = LoadInitialConditions; 
% load model parameters
modelparameters = LoadParameters;

AngII100 = [ti:0.01:(tf+1); ti:0.01:(tf+1)]';
AngII100(AngII100(:,1)<0,2) = 0;
AngII100(AngII100(:,1)>0,2) = 0.1;
% for step response comment out the following
%AngII100(AngII100(:,1)>300,2) = 0;

y1 = abs (y0);

% run simuations
[t, y] = ode15s(@odemodel, tspan, y1, options, modelparameters, AngII100);

% sampling the membrane voltage
[tp_fr fr index] = freq(t,y(:,179));

firing_rate = interp1(tp_fr, fr,tspan);

% plot the firing rate
plot(tspan,firing_rate)
ylabel('Firing rate (Hz)');
xlabel('Time (s)');

toc

end



Loading data, please wait...