neuron_RS2.m

%   This MATLAB file generates figure 1 in the paper by 
%               Izhikevich E.M. (2004) 
%   Which Model to Use For Cortical Spiking Neurons? 
%   use MATLAB R13 or later. November 2003. San Diego, CA 

%   Modified by Ali Minai


%%%%%%%%%%%%%%% regular spiking %%%%%%%%%%%%%%%%%%%%%% 

steps = 1000;                  %This simulation runs for 1000 steps

a=0.02; b=0.25; c=-65;  d=6;
V=-64; u=b*V;
VV=[];  uu=[];
tau = 0.25; 
tspan = 0:tau:steps;  %tau is the discretization time-step
                                  %tspan is the simulation interval
                                
T1=50;            %T1 is the time at which the step input rises
spike_ts = [];

for t=tspan
    if (t>T1) 
        I=1.0;     % This is the input which you will change in your simulation
    else
        I=0;
    end;
    V = V + tau*(0.04*V^2+5*V+140-u+I);
    u = u + tau*a*(b*V-u);
    if V > 30                 %if this is a spike
        VV(end+1)=30;         %VV is the time-series of membrane potentials
        V = c;
        u = u + d;
        spike_ts = [spike_ts ; 1];   %records a spike
    else
        VV(end+1)=V;
        spike_ts = [spike_ts ; 0];   %records no spike
    end;
    uu(end+1)=u;
end;

subplot(2,1,1)
plot(tspan,VV);                   %VV is plotted as the output
axis([0 max(tspan) -90 40])
xlabel('time step');
ylabel('V_m')
xticks([0 max(tspan)]);
xticklabels([0 steps]);
title('Regular Spiking');

subplot(2,1,2)
plot(tspan,spike_ts,'r');                   %spike train is plotted
axis([0 max(tspan) 0 1.5])
xlabel('time step');
xticks([0 max(tspan)]);
xticklabels([0 steps]);
yticks([0 1]);