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 ProbAMPANMDA2  
        RANGE tau_r_AMPA, tau_d_AMPA, tau_r_NMDA, tau_d_NMDA
        RANGE Use, u, Dep, Fac, u0, weight_NMDA
        RANGE i, iampa, inmda, g_AMPA, g_NMDA, e, initW
        NONSPECIFIC_CURRENT iampa,inmda
}

PARAMETER {

        tau_r_AMPA = 0.2   (ms)  : dual-exponential conductance profile
        tau_d_AMPA = 1.7    (ms)  : IMPORTANT: tau_r < tau_d
	tau_r_NMDA = 0.29   (ms) : dual-exponential conductance profile
        tau_d_NMDA = 43     (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
	mg = 1   (mM)  : initial concentration of mg2+
        mggate
    	initW = .001 (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
   
  

ASSIGNED {

        v (mV)
        i (nA)
	iampa (nA)
	inmda (nA)
        g_AMPA (uS)
	g_NMDA (uS)
        factor_AMPA
	factor_NMDA
	weight_NMDA
}

STATE {

        A_AMPA       : AMPA state variable to construct the dual-exponential profile - decays with conductance tau_r_AMPA
        B_AMPA       : AMPA state variable to construct the dual-exponential profile - decays with conductance tau_d_AMPA
	A_NMDA       : NMDA state variable to construct the dual-exponential profile - decays with conductance tau_r_NMDA
        B_NMDA       : NMDA state variable to construct the dual-exponential profile - decays with conductance tau_d_NMDA
}

INITIAL{

        LOCAL tp_AMPA, tp_NMDA
        
	A_AMPA = 0
        B_AMPA = 0
	
	A_NMDA = 0
	B_NMDA = 0
        
	tp_AMPA = (tau_r_AMPA*tau_d_AMPA)/(tau_d_AMPA-tau_r_AMPA)*log(tau_d_AMPA/tau_r_AMPA) :time to peak of the conductance
	tp_NMDA = (tau_r_NMDA*tau_d_NMDA)/(tau_d_NMDA-tau_r_NMDA)*log(tau_d_NMDA/tau_r_NMDA) :time to peak of the conductance
        
	factor_AMPA = -exp(-tp_AMPA/tau_r_AMPA)+exp(-tp_AMPA/tau_d_AMPA) :AMPA Normalization factor - so that when t = tp_AMPA, gsyn = gpeak
        factor_AMPA = 1/factor_AMPA
	
	factor_NMDA = -exp(-tp_NMDA/tau_r_NMDA)+exp(-tp_NMDA/tau_d_NMDA) :NMDA Normalization factor - so that when t = tp_NMDA, gsyn = gpeak
        factor_NMDA = 1/factor_NMDA
   
}

BREAKPOINT {

        SOLVE state METHOD cnexp
	mggate = 1 / (1 + exp(0.08  (/mV) * -(v)) * (mg / 3.57 (mM))) :mggate kinetics - Jahr & Stevens 1990
        g_AMPA = initW*.001*(B_AMPA-A_AMPA) :compute time varying conductance as the difference of state variables B_AMPA and A_AMPA
	g_NMDA = initW*.001*(B_NMDA-A_NMDA) * mggate :compute time varying conductance as the difference of state variables B_NMDA and A_NMDA and mggate kinetics
        iampa = g_AMPA*(v-e) :compute the AMPA driving force based on the time varying conductance, membrane potential, and AMPA reversal
	inmda = g_NMDA*(v-e) :compute the NMDA driving force based on the time varying conductance, membrane potential, and NMDA reversal
	i = iampa + inmda
}

DERIVATIVE state{

        A_AMPA' = -A_AMPA/tau_r_AMPA
        B_AMPA' = -B_AMPA/tau_d_AMPA
	A_NMDA' = -A_NMDA/tau_r_NMDA
        B_NMDA' = -B_NMDA/tau_d_NMDA
}


NET_RECEIVE (weight,weight_AMPA, weight_NMDA, Pv, Pr, u, tsyn (ms)){
	
	weight_AMPA = weight
	weight_NMDA = weight
     	A_AMPA = A_AMPA + weight_AMPA*factor_AMPA
        B_AMPA = B_AMPA + weight_AMPA*factor_AMPA
	A_NMDA = A_NMDA + weight_NMDA*factor_NMDA
        B_NMDA = B_NMDA + weight_NMDA*factor_NMDA

	:printf("NMDA weight = %g\n", weight_NMDA)

        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
                
		   
	
                    A_AMPA = A_AMPA + weight_AMPA*factor_AMPA
                    B_AMPA = B_AMPA + weight_AMPA*factor_AMPA
		    A_NMDA = A_NMDA + weight_NMDA*factor_NMDA
                    B_NMDA = B_NMDA + weight_NMDA*factor_NMDA

                
}