TITLE AMPA and NMDA receptor with presynaptic short-term plasticity
COMMENT
AMPA and NMDA receptor conductance using a dual-exponential profile
presynaptic short-term plasticity based on Fuhrmann et al. 2002
Implemented by Srikanth Ramaswamy, Blue Brain Project, July 2009
Etay: changed weight to be equal for NMDA and AMPA, gmax accessible in Neuron
ENDCOMMENT
NEURON {
POINT_PROCESS ProbUDFsyn2
RANGE tau_r, tau_d
RANGE Use, u, Dep, Fac, u0
RANGE i, g, e, gmax
NONSPECIFIC_CURRENT i
POINTER rng
}
PARAMETER {
tau_r = 0.2 (ms) : dual-exponential conductance profile
tau_d = 1.7 (ms) : IMPORTANT: tau_r < tau_d
Use = 1.0 (1) : Utilization of synaptic efficacy (just initial values! Use, Dep and Fac are overwritten by BlueBuilder assigned values)
Dep = 100 (ms) : relaxation time constant from depression
Fac = 10 (ms) : relaxation time constant from facilitation
e = 0 (mV) : AMPA and NMDA reversal potential
gmax = .001 (uS) : weight conversion factor (from nS to uS)
u0 = 0 :initial value of u, which is the running value of Use
}
COMMENT
The Verbatim block is needed to generate random nos. from a uniform distribution between 0 and 1
for comparison with Pr to decide whether to activate the synapse or not
ENDCOMMENT
VERBATIM
#include
#include
#include
double nrn_random_pick(void* r);
void* nrn_random_arg(int argpos);
ENDVERBATIM
ASSIGNED {
v (mV)
i (nA)
g (uS)
factor
rng
weight_NMDA
}
STATE {
A : state variable to construct the dual-exponential profile - decays with conductance tau_r_AMPA
B : state variable to construct the dual-exponential profile - decays with conductance tau_d_AMPA
}
INITIAL{
LOCAL tp
A = 0
B = 0
tp = (tau_r*tau_d)/(tau_d-tau_r)*log(tau_d/tau_r) :time to peak of the conductance
factor = -exp(-tp/tau_r)+exp(-tp/tau_d) : Normalization factor - so that when t = tp, gsyn = gpeak
factor = 1/factor
}
BREAKPOINT {
SOLVE state METHOD cnexp
g = gmax*(B-A) :compute time varying conductance as the difference of state variables B and A
i = g*(v-e) :compute the driving force based on the time varying conductance, membrane potential, and reversal
}
DERIVATIVE state{
A' = -A/tau_r
B' = -B/tau_d
}
NET_RECEIVE (weight, Pv, Pr, u, tsyn (ms)){
INITIAL{
Pv=1
u=u0
tsyn=t
}
: calc u at event-
if (Fac > 0) {
u = u*exp(-(t - tsyn)/Fac) :update facilitation variable if Fac>0 Eq. 2 in Fuhrmann et al.
} else {
u = Use
}
if(Fac > 0){
u = u + Use*(1-u) :update facilitation variable if Fac>0 Eq. 2 in Fuhrmann et al.
}
Pv = 1 - (1-Pv) * exp(-(t-tsyn)/Dep) :Probability Pv for a vesicle to be available for release, analogous to the pool of synaptic
:resources available for release in the deterministic model. Eq. 3 in Fuhrmann et al.
Pr = u * Pv :Pr is calculated as Pv * u (running value of Use)
Pv = Pv - u * Pv :update Pv as per Eq. 3 in Fuhrmann et al.
:printf("Pv = %g\n", Pv)
:printf("Pr = %g\n", Pr)
tsyn = t
if (erand() < Pr){
A = A + weight*factor
B = B + weight*factor
}
}
PROCEDURE setRNG() {
VERBATIM
{
/**
* This function takes a NEURON Random object declared in hoc and makes it usable by this mod file.
* Note that this method is taken from Brett paper as used by netstim.hoc and netstim.mod
* which points out that the Random must be in negexp(1) mode
*/
void** pv = (void**)(&_p_rng);
if( ifarg(1)) {
*pv = nrn_random_arg(1);
} else {
*pv = (void*)0;
}
}
ENDVERBATIM
}
FUNCTION erand() {
VERBATIM
//FILE *fi;
double value;
if (_p_rng) {
/*
:Supports separate independent but reproducible streams for
: each instance. However, the corresponding hoc Random
: distribution MUST be set to Random.negexp(1)
*/
value = nrn_random_pick(_p_rng);
//fi = fopen("RandomStreamMCellRan4.txt", "w");
//fprintf(fi,"random stream for this simulation = %lf\n",value);
//printf("random stream for this simulation = %lf\n",value);
return value;
}else{
ENDVERBATIM
: the old standby. Cannot use if reproducible parallel sim
: independent of nhost or which host this instance is on
: is desired, since each instance on this cpu draws from
: the same stream
erand = exprand(1)
VERBATIM
}
ENDVERBATIM
erand = value
}