XPP model

This model was converted from XPP ode format to SBML using sbmlutils-0.1.5a6.

# Wang-Buzsaki neuron network with 50E-cells and 20I-cells with all-to-all 
# connectivity with heterogeneity with tonic input for 1 sec 

table Ir % 50 0 49 ran(1)*0.5
@ autoeval=0
wiener ze[0..49]
wiener zi[0..19]
#
# Parameters used
p gKLe=0.12, gNaL=0.017, gKLi=0.15
p gK=9.0, gNa=35.0
p ENa=55.0, EK=-90.0
p gei=0.6, gee=0.05, gie=0.6, gii=0.10
p sige=1.2,sigi=1.2
p phi=5.0
p Vsyni=-75,Vti=2,Vsi=5,alphai=5,betai=.1,tmaxi=1
p Vsyne=0,Vte=2,Vse=5,alphae=1.1,betae=.19,tmaxe=1
p Vlth=-25,Vshp=5
#
# Tonic input description and parameters
Iapp[0..49]=I0+I1*Ir([j])
p I0=2.5,I1=2
#
aveVE=(sum(0,49)of(shift(Ve0,i')))/50
inputse=sum(0,49)of(shift(se0,i'))/50
inputsi=sum(0,19)of(shift(si0,i'))/20
#
#ODEs for e-cells
Ve[0..49]'=Iapp[j]-gKLe*(Ve[j]-EK)-gNaL*(Ve[j]-ENa)-gNa*(Minf(ve[j])^3)*he[j]*(Ve[j]-ENa)-gK*(ne[j]^4)*(Ve[j]-EK)-gie*inputsi*(Ve[j]-Vsyni)-gee*inputse*(Ve[j]-Vsyne)-ica(ve[j])-iahp(ca[j],ve[j])+sige*ze[j]
he[0..49]'=phi*(Hinf(ve[j])-he[j])/tauH(ve[j])
ne[0..49]'=phi*(Ninf(ve[j])-ne[j])/tauN(ve[j])
se[0..49]'=alphae*ke(ve[j])*(1-se[j])-betae*se[j]
#
#ODEs for i-cells
Vi[0..19]'=-gKLi*(Vi[j]-EK)-gNaL*(Vi[j]-ENa)-gNa*(Minf(vi[j])^3)*hi[j]*(Vi[j]-ENa)-gK*(ni[j]^4)*(Vi[j]-EK)-gei*inputse*(Vi[j]-Vsyne)-gii*inputsi*(Vi[j]-Vsyni)+sigi*zi[j]
hi[0..19]'=phi*(Hinf(vi[j])-hi[j])/tauH(vi[j])
ni[0..19]'=phi*(Ninf(vi[j])-ni[j])/tauN(vi[j])
si[0..19]'=alphai*ki(vi[j])*(1-si[j])-betai*si[j]
#
ki(x)=tmaxi/(1+exp(-(x-vti)/vsi))
ke(y)=tmaxe/(1+exp(-(y-vte)/vse))
#
# Spike frequency adaptation description with parameters
# calcium
mlinf(v)=1/(1+exp(-(v-vlth)/vshp))
ica(v)=gca*mlinf(v)*(v-eca)
ca[0..49]'=(-alpha*ica(ve[j])-ca[j]/tauca)
# k-ca
iahp(ca,v)=gahp*(ca/(ca+kd))*(v-Ek)
# corresponding parameters
p kd=30, Eca=120
p alpha=.002, tauca=80, gca=1, gahp=3
#
#
alpham(v)=0.1*(V+35.0)/(1.0-exp(-(V+35.0)/10.0))
betam(v)=4.0*exp(-(V+60.0)/18.0)
Minf(v)=alpham(v)/(alpham(v)+betam(v))
#
alphah(v)= 0.07*exp(-(V+58.0)/20.0)
betah(v)=1.0/(1.0+exp(-(V+28.0)/10.0))
Hinf(v)=alphah(v)/(alphah(v)+betah(v))
tauH(v)=1.0/(alphah(v)+betah(v))
#
alphan(v)=0.01*(V+34.0)/(1.0-exp(-(V+34.0)/10.00))
betan(v)=0.125*exp(-(V+44.0)/80.0)
Ninf(v)=alphan(v)/(alphan(v)+betan(v))
tauN(v)=1.0/(alphan(v)+betan(v))
#
# Initial conditions
init Ve[0..49]=-64
init he[0..49]=0.78
init ne[0..49]=0.09
init Vi[0..19]=-64
init hi[0..19]=0.78
init ni[0..19]=0.09
#
# Creating some auxiliary variables
aux aveSE=inputse
auc aveSI=inputsi
aux LFP=aveVE
#
# Numerics description
@ XP=T
@ YP=LFP
@ autoeval=0
@ TOTAL=1400,trans=400
@ nOut=10  
@ DT=0.01,bound=100000,maxstor=1000000
@ METH=euler
@ TOLER=0.00001
@ XLO=0.0, XHI=30.0, YLO=-90.0, YHI=30.0
done
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Copyright © 2017 Matthias Koenig

Redistribution and use of any part of this model, with or without modification, are permitted provided that the following conditions are met:

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This model is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.


Model :

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time
substance
extent
volume
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length
Access SBML model  L3V1

FunctionDefinitions [20] name math sbo cvterm
max minimum x y x x y y
min maximum x y x x y y
heav heavyside x 0 x 0 0.5 x 0 1 x 0 0
mod modulo x y x y x y x 0 y 0 x y x y
ki x tmaxi vsi vti tmaxi 1 x vti vsi
ke y tmaxe vse vte tmaxe 1 y vte vse
mlinf v vlth vshp 1 1 v vlth vshp
ica v eca gca vlth vshp gca mlinf v vshp vlth v eca
iahp ca v ek gahp kd gahp ca ca kd v ek
alpham v 0.1 v 35 1 v 35 10
betam v 4 v 60 18
minf v alpham v alpham v betam v
alphah v 0.07 v 58 20
betah v 1 1 v 28 10
hinf v alphah v alphah v betah v
tauh v 1 alphah v betah v
alphan v 0.01 v 34 1 v 34 10
betan v 0.125 v 44 80
ninf v alphan v alphan v betan v
taun v 1 alphan v betan v

Parameters [61] name constant value unit derived unit sbo cvterm
0.0 None
0.0 None
gkle gkle = 0.12 0.12 None
gnal gnal = 0.017 0.017 None
gkli gkli = 0.15 0.15 None
gk gk = 9.0 9.0 None
gna gna = 35.0 35.0 None
ena ena = 55.0 55.0 None
ek ek = -90.0 -90.0 None
gei gei = 0.6 0.6 None
gee gee = 0.05 0.05 None
gie gie = 0.6 0.6 None
gii gii = 0.10 0.1 None
sige sige = 1.2 1.2 None
sigi sigi = 1.2 1.2 None
phi phi = 5.0 5.0 None
vsyni vsyni = -75 -75.0 None
vti vti = 2 2.0 None
vsi vsi = 5 5.0 None
alphai alphai = 5 5.0 None
betai betai = .1 0.1 None
tmaxi tmaxi = 1 1.0 None
vsyne vsyne = 0 0.0 None
vte vte = 2 2.0 None
vse vse = 5 5.0 None
alphae alphae = 1.1 1.1 None
betae betae = .19 0.19 None
tmaxe tmaxe = 1 1.0 None
vlth vlth = -25 -25.0 None
vshp vshp = 5 5.0 None
i0 i0 = 2.5 2.5 None
i1 i1 = 2 2.0 None
kd kd = 30 30.0 None
eca eca = 120 120.0 None
alpha alpha = .002 0.002 None
tauca tauca = 80 80.0 None
gca gca = 1 1.0 None
gahp gahp = 3 3.0 None
ve[0..49] = -64 -64.0 None
he[0..49] = 0.78 0.78 None
ne[0..49] = 0.09 0.09 None
vi[0..19] = -64 -64.0 None
hi[0..19] = 0.78 0.78 None
ni[0..19] = 0.09 0.09 None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
0.0 dimensionless None
aveve 0.0 dimensionless None
inputse 0.0 dimensionless None
inputsi 0.0 dimensionless None
avese 0.0 dimensionless None
avesi 0.0 dimensionless None
lfp 0.0 dimensionless None
t model time 0.0 dimensionless None

Rules [17]   assignment name derived units sbo cvterm
= None None
= None None
= None None
= None None
= None None
= None None
= None None
= None None
= None None
= None None
aveve = None None
inputse = None None
inputsi = None None
avese = inputse None
avesi = inputsi None
lfp = aveve None
t = time None