# Morris-Lecar model Methods Chapter wiener nn dv/dt = ( I - gca*minf(V)*(V-Vca)-gk*w*(V-VK)-gl*(V-Vl))/c+sig*nn dw/dt = phi*(winf(V)-w)/tauw(V) v(0)=-16 w(0)=0.014915 minf(v)=.5*(1+tanh((v-v1)/v2)) winf(v)=.5*(1+tanh((v-v3)/v4)) tauw(v)=1/cosh((v-v3)/(2*v4)) param vk=-84,vl=-60,vca=120 param i=90,sig=1,gk=8,gl=2,c=20 param v1=-1.2,v2=18 # Uncomment the ones you like!! par1-3 v3=2,v4=30,phi=.04,gca=4.4 #par4-6 v3=12,v4=17.4,phi=.06666667,gca=4 #par7-8 v3=12,v4=17.4,phi=.23,gca=4 @ total=500000,dt=.25,xlo=-75,xhi=75,ylo=-.25,yhi=.5,xp=v,yp=w,meth=euler @ maxstor=10000000,trans=10000 done 1. Numerics Poincare Period variable:w section:0.4 direction: 1 stop on sect: N click OK and then Esc 2. Initial Conds Go you will have about 4000 data points to use excel or something, open the Data viewer and click on write to save the data in ascii format. The first column contains the ISIs 3. In XPP, click on Numerics stochastic histogram NBINS: 100 Low:0 Hi:1000 Variable: t Condition: Esc to main meneu; then plot V vs t you can change total time to get more points if you want