TITLE AMPA and NMDA receptor with short-term plasticity
COMMENT
Conductance-based AMPA-NMDA synaptic current with Wang-type of short-term synaptic depression
Implementation by Tuomo Maki-Marttunen, 2016
Tuomo 2021: removed depression
ENDCOMMENT
NEURON {
POINT_PROCESS AMPANMDA
RANGE gAMPAmax, gNMDAmax, MgCon
RANGE E_Glu, tau_sAMPA, tau_sNMDA, tau_xNMDA, alphas
RANGE i, i_AMPA, i_NMDA, g_AMPA, g_NMDA, sAMPA, sNMDA, xNMDA
NONSPECIFIC_CURRENT i, i_AMPA,i_NMDA
}
PARAMETER {
gAMPAmax = 0.01 (uS)
gNMDAmax = 0.007 (uS)
MgCon = 0.69
mggate
E_Glu = 0 (mV)
tau_sAMPA = 2 (ms)
tau_sNMDA = 100 (ms)
tau_xNMDA = 2 (ms)
alphas = 0.5 (kHz)
}
ASSIGNED {
v (mV)
i (nA)
i_AMPA (nA)
i_NMDA (nA)
g_AMPA (uS)
g_NMDA (uS)
}
STATE {
sAMPA : AMPA state variable to construct the single-exponential profile - decays with conductance tau_sAMPA
sNMDA : NMDA state variable to construct the dual-exponential profile - decays with conductance tau_sAMPA
xNMDA : NMDA state variable to construct the dual-exponential profile - decays with conductance tau_xAMPA
}
INITIAL{
sAMPA = 0
sNMDA = 0
xNMDA = 0
}
BREAKPOINT {
SOLVE state METHOD cnexp
if (sNMDA > 1) { :Do not allow larger values than 1
sNMDA = 1
}
mggate = 1 / (1 + exp(0.062 (/mV) * -(v)) * (MgCon / 3.57 (mM))) :mggate kinetics - Jahr & Stevens 1990
g_AMPA = gAMPAmax*sAMPA :compute time varying conductance
g_NMDA = gNMDAmax*sNMDA * mggate :compute time varying conductance using mggate kinetics
i_AMPA = g_AMPA*(v-E_Glu) :compute the AMPA driving force based on the time varying conductance, membrane potential, and AMPA reversal
i_NMDA = g_NMDA*(v-E_Glu) :compute the NMDA driving force based on the time varying conductance, membrane potential, and NMDA reversal
i = i_AMPA + i_NMDA
}
DERIVATIVE state{
sAMPA' = -sAMPA/tau_sAMPA
sNMDA' = -sNMDA/tau_sNMDA + alphas*xNMDA*(1-sNMDA)
xNMDA' = -xNMDA/tau_xNMDA
}
:NET_RECEIVE (weight, Pv, Pr, u, tsyn (ms)){
NET_RECEIVE (weight){
sAMPA = sAMPA + 1
xNMDA = xNMDA + 1
if (sAMPA > 1) { :Do not allow larger values than 1
sAMPA = 1
}
}