: inhibitory synapses with both GABAa and GABAb
NEURON {
POINT_PROCESS inter2pyr
NONSPECIFIC_CURRENT i_gabab, i_gabaa
RANGE initW
RANGE Cdur_gabab, AlphaTmax_gabab, Beta_gabab, Erev_gabab, gbar_gabab, W_gabab, on_gabab, g_gabab, K3_gabab, K4_gabab, n_gabab, Kd_gabab, rr_gabab
RANGE Cdur_gabaa, AlphaTmax_gabaa, Beta_gabaa, Erev_gabaa, gbar_gabaa, W_gabaa, on_gabaa, g_gabaa
RANGE ECa, ICa, P0a, P0b, fCa, tauCa, iCatotal
RANGE Cainf, pooldiam, z
RANGE lambda1, lambda2, threshold1, threshold2
RANGE fmax, fmin, Wmax, Wmin, maxChange, normW, scaleW
RANGE pregid,postgid
:Added by Ali
RANGE F, f, tauF, D1, d1, tauD1, D2, d2, tauD2, facfactor
RANGE aACH, bACH, aDA, bDA, wACH, wDA
}
UNITS {
(mV) = (millivolt)
(nA) = (nanoamp)
(uS) = (microsiemens)
FARADAY = 96485 (coul)
pi = 3.141592 (1)
}
PARAMETER {
initW = 5
Cdur_gabaa = 5.31 (ms)
AlphaTmax_gabaa = 5000 (/ms)
Beta_gabaa = 0.18(/ms) :0.072
Erev_gabaa = -75 (mV)
gbar_gabaa = 1.7e-3 (uS)
Cdur_gabab = 6 (ms)
AlphaTmax_gabab = 0.09 (/ms mM) :.08
Beta_gabab = 0.008 (/ms) :0.008
Erev_gabab = -75 (mV)
gbar_gabab = 1e-3 (uS)
K3_gabab = .18 (/ms)
K4_gabab = .034 (/ms)
n_gabab = 4
Kd_gabab = 100
ECa = 120
gbar_Ca = 18e-3 (uS)
Cainf = 50e-6 (mM)
pooldiam = 1.8172 (micrometer)
z = 2
tauCa = 50 (ms)
P0a = .0035 : Had to lower 10 fold becaues for some reason inh synapses generated 10 folds more calcium than exitatory despite simlar levels of NMDA and GABAb.
P0b = .0015
fCa = .024
lambda1 = 2.5
lambda2 = .01
threshold1 = 0.2 (uM)
threshold2 = 0.4 (uM)
:fmax = 3
:fmin = .8
:Added by Ali
ACH = 1
LearningShutDown = 1
facfactor = 1
: the (1) is needed for the range limits to be effective
f = 1 (1) < 0, 1e9 > : facilitation
tauF = 1 (ms) < 1e-9, 1e9 >
d1 = 1 (1) < 0, 1 > : fast depression
tauD1 = 1 (ms) < 1e-9, 1e9 >
d2 = 1 (1) < 0, 1 > : slow depression
tauD2 = 1 (ms) < 1e-9, 1e9 >
aACH = 1
bACH = 0
wACH = 0
aDA = 1
bDA = 0
wDA = 0
}
ASSIGNED {
v (mV)
i_gabab (nA)
g_gabab (uS)
on_gabab
W_gabab
rr_gabab
i_gabaa (nA)
g_gabaa (uS)
on_gabaa
W_gabaa
t0 (ms)
ICa (mA)
Afactor (mM/ms/nA)
iCatotal (mA)
dW_gabaa
Wmax
Wmin
maxChange
normW
scaleW
pregid
postgid
tsyn
fa
F
D1
D2
}
STATE { r_gabab s_gabab r_gabaa Capoolcon }
INITIAL {
on_gabab = 0
r_gabab = 0
s_gabab = 0
W_gabab = initW
on_gabaa = 0
r_gabaa = 0
W_gabaa = initW
t0 = -1
:Wmax = fmax*initW
:Wmin = fmin*initW
maxChange = (Wmax-Wmin)/10
dW_gabaa = 0
Capoolcon = Cainf
Afactor = 1/(z*FARADAY*4/3*pi*(pooldiam/2)^3)*(1e6)
:Added by Ali printf("Afactor : %g", Afactor)
tsyn = -1e30
fa =0
F = 1
D1 = 1
D2 = 1
}
BREAKPOINT {
SOLVE release METHOD cnexp
}
DERIVATIVE release {
if (t0>0) {
if (t-t0 < Cdur_gabab) {
on_gabab = 1
} else {
on_gabab = 0
}
if (t-t0 < Cdur_gabaa) {
on_gabaa = 1
} else {
on_gabaa = 0
}
}
r_gabab' = AlphaTmax_gabab*on_gabab*(1-r_gabab)-Beta_gabab*r_gabab
s_gabab' = K3_gabab*r_gabab-K4_gabab*s_gabab
r_gabaa' = AlphaTmax_gabaa*on_gabaa*(1-r_gabaa)-Beta_gabaa*r_gabaa
dW_gabaa = eta(Capoolcon)*(lambda1*omega(Capoolcon, threshold1, threshold2)-lambda2*W_gabaa)*dt
: Limit for extreme large weight changes
if (fabs(dW_gabaa) > maxChange) {
if (dW_gabaa < 0) {
dW_gabaa = -1*maxChange
} else {
dW_gabaa = maxChange
}
}
:Normalize the weight change
normW = (W_gabaa-Wmin)/(Wmax-Wmin)
if (dW_gabaa < 0) {
scaleW = sqrt(fabs(normW))
} else {
scaleW = sqrt(fabs(1.0-normW))
}
W_gabaa = W_gabaa + dW_gabaa*scaleW *(1+ (wACH * (ACH - 1))) * LearningShutDown
:Weight value limits
if (W_gabaa > Wmax) {
W_gabaa = Wmax
} else if (W_gabaa < Wmin) {
W_gabaa = Wmin
}
rr_gabab = s_gabab^n_gabab/(s_gabab^n_gabab+Kd_gabab)
g_gabab = gbar_gabab*rr_gabab * facfactor
i_gabab = W_gabab*g_gabab*(v - Erev_gabab)
g_gabaa = gbar_gabaa*r_gabaa * facfactor
i_gabaa = W_gabaa*g_gabaa*(v - Erev_gabaa) * (1 + (bACH * (ACH-1)))
ICa = P0b*g_gabab*(v - ECa) + P0a * gbar_Ca*VDCCm(v) * ( v - ECa) :P0b
Capoolcon'= -fCa*Afactor*ICa + (Cainf-Capoolcon)/tauCa
}
NET_RECEIVE(dummy_weight) {
:Added by Ali, Synaptic facilitation
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)
tsyn = t
facfactor = F * D1 * D2
F = F * f
D1 = D1 * d1
D2 = D2 * d2
:printf("\t%g\t%g\t%g\n", F, D1, D2)
t0 = t :Spike time for conductance openining.
}
:::::::::::: FUNCTIONs and PROCEDUREs ::::::::::::
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 VDCCm (v (mV)) {
UNITSOFF
VDCCm = 1 / (1 + exp( (-4 - v)/6.3)) : Values taken from Fisher et al. 1990 from the 14pS channel group "Properties and distribution of single voltage..."
UNITSON
}
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))}
}