This model was converted from XPP ode format to SBML using sbmlutils-0.1.5a6.
# 200 e and 50 I HH equations
# random applied current, random conductances
# to get it started, just set the excitatory synapses
# to some random values between 0 and 1
# you will get persistent activity.
# here are the HH functions
am(v)=phi*.1*(v+40)/(1-exp(-(v+40)/10))
bm(v)=phi*4*exp(-(v+65)/18)
ah(v)=phi*.07*exp(-(v+65)/20)
bh(v)=phi*1/(1+exp(-(v+35)/10))
an(v)=phi*.01*(v+55)/(1-exp(-(v+55)/10))
bn(v)=phi*.125*exp(-(v+65)/80)
par phi=1
# this is the current for each cell
ihh(v,m,h,n)=gna*h*(v-vna)*m^3+gk*(v-vk)*n^4+gl*(v-vl)
# synaptic onset parameters
# s' = a(vpre)(1-s)-s/tau
ae(x)=ae0/(1+exp(-x/5))
ai(x)=ai0/(1+exp(-x/5))
par ae0=4,ai0=1
# dont recompute the random tables every time a parameter is changed
@ autoeval=0
# random synapses - 20 % connectivity
table wee % 40000 0 39999 ran(1)<.02
table wei % 10000 0 9999 ran(1)<.02
table wie % 10000 0 9999 ran(1)<.02
table wii % 2500 0 2499 ran(1)<.02
# multiply synapses by weights
special see=mmult(200,200,wee,se0)
special sei=mmult(200,50,wei,se0)
special sie=mmult(50,200,wie,si0)
special sii=mmult(50,50,wii,si0)
# random currents applied to each cell
table r_e % 200 0 199 ran(1)-.5
table r_i % 50 0 49 ran(1)-.5
# parameters
par taue=4,taui=10
par vna=50 vk=-77 vl=-54.4 gna=120 gk=36 gl=0.3
par ie0=10,ie1=0
par ii0=10,ii1=0
par gee=0,gie=0,gii=0,gei=0
par eex=0,ein=-75
# finally the ODEs
ve[0..199]'=ie0+ie1*r_e([j])-ihh(ve[j],me[j],he[j],ne[j])-gee*see([j])*(ve[j]-eex)-gie*sie([j])*(ve[j]-ein)
vi[0..49]'=ii0+ii1*r_i([j])-ihh(vi[j],mi[j],hi[j],ni[j])-gei*sei([j])*(vi[j]-eex)-gii*sii([j])*(vi[j]-ein)
# synapses...
se[0..199]'=-se[j]/taue+ae(ve[j])*(1-se[j])
si[0..49]'=-si[j]/taui+ai(vi[j])*(1-si[j])
# gating variables
me[0..199]'=am(ve[j])*(1-me[j])-bm(ve[j])*me[j]
he[0..199]'=ah(ve[j])*(1-he[j])-bh(ve[j])*he[j]
ne[0..199]'=an(ve[j])*(1-ne[j])-bn(ve[j])*ne[j]
mi[0..49]'=am(vi[j])*(1-mi[j])-bm(vi[j])*mi[j]
hi[0..49]'=ah(vi[j])*(1-hi[j])-bh(vi[j])*hi[j]
ni[0..49]'=an(vi[j])*(1-ni[j])-bn(vi[j])*ni[j]
# initial data
init ve[0..199]=-65
init vi[0..49]=-65
# some numerical settings
@ total=200,meth=euler,nout=10,dt=.01
done
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