:Pyramidal Cells to Interneuron Cells AMPA+NMDA with local Ca2+ pool
NEURON {
POINT_PROCESS pyrD2interV_STFD
USEION ca READ eca
NONSPECIFIC_CURRENT inmda, iampa
RANGE initW
RANGE Cdur_nmda, AlphaTmax_nmda, Beta_nmda, Erev_nmda, gbar_nmda, W_nmda, on_nmda, g_nmda
RANGE Cdur_ampa, AlphaTmax_ampa, Beta_ampa, Erev_ampa, gbar_ampa, W, on_ampa, g_ampa
RANGE eca, ICan, P0n, fCan, tauCa, Icatotal
RANGE ICaa, P0a, fCaa
RANGE Cainf, pooldiam, z
RANGE lambda1, lambda2, threshold1, threshold2
RANGE fmax, fmin, Wmax, Wmin, maxChange, normW, scaleW, srcid, destid
RANGE pregid,postgid, thr_rp
RANGE F, f, tauF, D1, d1, tauD1, D2, d2, tauD2
RANGE facfactor
}
UNITS {
(mV) = (millivolt)
(nA) = (nanoamp)
(uS) = (microsiemens)
FARADAY = 96485 (coul)
pi = 3.141592 (1)
}
PARAMETER {
srcid = -1 (1)
destid = -1 (1)
Cdur_nmda = 16.7650 (ms)
AlphaTmax_nmda = .2659 (/ms)
Beta_nmda = 0.008 (/ms)
Erev_nmda = 0 (mV)
gbar_nmda = .5e-3 (uS)
Cdur_ampa = 0.713 (ms)
AlphaTmax_ampa = 10.1571 (/ms)
Beta_ampa = 0.4167 (/ms)
Erev_ampa = 0 (mV)
gbar_ampa = 1e-3 (uS)
eca = 120
Cainf = 50e-6 (mM)
pooldiam = 1.8172 (micrometer)
z = 2
tauCa = 50 (ms)
P0n = .015
fCan = .024
P0a = .001
fCaa = .024
lambda1 = 3
lambda2 = .01
threshold1 = 0.35 : 0.4 : 0.45 :0.5 (uM)
threshold2 = 0.4 : 0.45 : 0.5 :0.6 (uM)
:AMPA Weight
initW = 1.5 :3 :1.5 :1
fmax = 3 : 2
fmin = .8
thr_rp = 1 : .7
facfactor = 1
: the (1) is needed for the range limits to be effective
f = 1 (1) < 0, 1e9 > : facilitation : 1.3 (1) < 0, 1e9 > : facilitation
tauF = 45 (ms) < 1e-9, 1e9 >
d1 = 0.95 (1) < 0, 1 >: 0.95 (1) < 0, 1 > : fast depression
tauD1 = 40 (ms) < 1e-9, 1e9 >
d2 = 0.9 (1) < 0, 1 > : 0.9 (1) < 0, 1 > : slow depression
tauD2 = 70 (ms) < 1e-9, 1e9 >
}
ASSIGNED {
v (mV)
inmda (nA)
g_nmda (uS)
on_nmda
W_nmda
iampa (nA)
g_ampa (uS)
on_ampa
W
t0 (ms)
ICan (mA)
ICaa (mA)
Afactor (mM/ms/nA)
Icatotal (mA)
dW_ampa
Wmax
Wmin
maxChange
normW
scaleW
pregid
postgid
rp
tsyn
fa
F
D1
D2
}
STATE { r_nmda r_ampa capoolcon }
INITIAL {
on_nmda = 0
r_nmda = 0
W_nmda = initW
on_ampa = 0
r_ampa = 0
W = initW
t0 = -1
Wmax = fmax*initW
Wmin = fmin*initW
maxChange = (Wmax-Wmin)/10
dW_ampa = 0
capoolcon = Cainf
Afactor = 1/(z*FARADAY*4/3*pi*(pooldiam/2)^3)*(1e6)
fa =0
F = 1
D1 = 1
D2 = 1
}
BREAKPOINT {
SOLVE release METHOD cnexp
}
DERIVATIVE release {
if (t0>0) {
if (rp < thr_rp) {
if (t-t0 < Cdur_nmda) {
on_nmda = 1
} else {
on_nmda = 0
}
if (t-t0 < Cdur_ampa) {
on_ampa = 1
} else {
on_ampa = 0
}
} else {
on_nmda = 0
on_ampa = 0
}
}
r_nmda' = AlphaTmax_nmda*on_nmda*(1-r_nmda)-Beta_nmda*r_nmda
r_ampa' = AlphaTmax_ampa*on_ampa*(1-r_ampa)-Beta_ampa*r_ampa
dW_ampa = eta(capoolcon)*(lambda1*omega(capoolcon, threshold1, threshold2)-lambda2*W)*dt
: Limit for extreme large weight changes
if (fabs(dW_ampa) > maxChange) {
if (dW_ampa < 0) {
dW_ampa = -1*maxChange
} else {
dW_ampa = maxChange
}
}
:Normalize the weight change
normW = (W-Wmin)/(Wmax-Wmin)
if (dW_ampa < 0) {
scaleW = sqrt(fabs(normW))
} else {
scaleW = sqrt(fabs(1.0-normW))
}
W = W + dW_ampa*scaleW
:Weight value limits
if (W > Wmax) {
W = Wmax
} else if (W < Wmin) {
W = Wmin
}
g_nmda = gbar_nmda*r_nmda*facfactor
inmda = W_nmda*g_nmda*(v - Erev_nmda)*sfunc(v)
g_ampa = gbar_ampa*r_ampa*facfactor
iampa = W*g_ampa*(v - Erev_ampa)
ICan = P0n*g_nmda*(v - eca)*sfunc(v)
ICaa = P0a*W*g_ampa*(v-eca)/initW
Icatotal = ICan + ICaa
capoolcon'= -fCan*Afactor*Icatotal + (Cainf-capoolcon)/tauCa
}
NET_RECEIVE(dummy_weight) {
t0 = t
rp = unirand()
:F = 1 + (F-1)* exp(-(t - tsyn)/tauF)
D1 = 1 - (1-D1)*exp(-(t - tsyn)/tauD1)
D2 = 1 - (1-D2)*exp(-(t - tsyn)/tauD2)
:printf("%g\t%g\t%g\t%g\t%g\t%g\n", t, t-tsyn, F, D1, D2, facfactor)
::printf("%g\t%g\t%g\t%g\n", F, D1, D2, facfactor)
tsyn = t
facfactor = F * D1 * D2
F = F * f
if (F > 2) {
F=2
}
if (facfactor < 0.7) {
facfactor=0.7
}
if (F < 0.8) {
F=0.8
}
D1 = D1 * d1
D2 = D2 * d2
:printf("\t%g\t%g\t%g\n", F, D1, D2)
}
:::::::::::: FUNCTIONs and PROCEDUREs ::::::::::::
FUNCTION sfunc (v (mV)) {
UNITSOFF
sfunc = 1/(1+0.33*exp(-0.06*v))
UNITSON
}
FUNCTION eta(Cani (mM)) {
LOCAL taulearn, P1, P2, P4, Cacon
P1 = 0.1
P2 = P1*1e-4
P4 = 1
Cacon = Cani*1e3
taulearn = P1/(P2+Cacon*Cacon*Cacon)+P4
eta = 1/taulearn*0.001
}
FUNCTION omega(Cani (mM), threshold1 (uM), threshold2 (uM)) {
LOCAL r, mid, Cacon
Cacon = Cani*1e3
r = (threshold2-threshold1)/2
mid = (threshold1+threshold2)/2
if (Cacon <= threshold1) { omega = 0}
else if (Cacon >= threshold2) { omega = 1/(1+50*exp(-50*(Cacon-threshold2)))}
else {omega = -sqrt(r*r-(Cacon-mid)*(Cacon-mid))}
}
FUNCTION unirand() { : uniform random numbers between 0 and 1
unirand = scop_random()
}