TITLE minimal model of GABAa receptors COMMENT ----------------------------------------------------------------------------- Minimal kinetic model for GABA-A receptors ========================================== Model of Destexhe, Mainen & Sejnowski, 1994: (closed) + T <-> (open) The simplest kinetics are considered for the binding of transmitter (T) to open postsynaptic receptors. The corresponding equations are in similar form as the Hodgkin-Huxley model: dr/dt = alpha * [T] * (1-r) - beta * r I = gmax * [open] * (V-Erev) where [T] is the transmitter concentration and r is the fraction of receptors in the open form. If the time course of transmitter occurs as a pulse of fixed duration, then this first-order model can be solved analytically, leading to a very fast mechanism for simulating synaptic currents, since no differential equation must be solved (see Destexhe, Mainen & Sejnowski, 1994). ----------------------------------------------------------------------------- Based on voltage-clamp recordings of GABAA receptor-mediated currents in rat hippocampal slices (Otis and Mody, Neuroscience 49: 13-32, 1992), this model was fit directly to experimental recordings in order to obtain the optimal values for the parameters (see Destexhe, Mainen and Sejnowski, 1996). ----------------------------------------------------------------------------- This mod file includes a mechanism to describe the time course of transmitter on the receptors. The time course is approximated here as a brief pulse triggered when the presynaptic compartment produces an action potential. The pointer "pre" represents the voltage of the presynaptic compartment and must be connected to the appropriate variable in oc. ----------------------------------------------------------------------------- See details in: Destexhe, A., Mainen, Z.F. and Sejnowski, T.J. An efficient method for computing synaptic conductances based on a kinetic model of receptor binding Neural Computation 6: 10-14, 1994. Destexhe, A., Mainen, Z.F. and Sejnowski, T.J. Kinetic models of synaptic transmission. In: Methods in Neuronal Modeling (2nd edition; edited by Koch, C. and Segev, I.), MIT press, Cambridge, 1996. Written by Alain Destexhe, Laval University, 1995 ----------------------------------------------------------------------------- ENDCOMMENT NEURON { POINT_PROCESS GABAb RANGE g, gmax, R NONSPECIFIC_CURRENT i GLOBAL Cmax, Cdur, Alpha, Beta, Erev, Rinf, Rtau RANGE i } UNITS { (nA) = (nanoamp) (mV) = (millivolt) (umho) = (micromho) (mM) = (milli/liter) } PARAMETER { Cmax = 10 (mM) : max transmitter concentration Cdur = 10 (ms) : transmitter duration (rising phase) Alpha = 0.001 (/ms mM) : forward (binding) rate Beta = 0.0047 (/ms) : backward (unbinding) rate Erev = -80 (mV) : reversal potential } ASSIGNED { v (mV) : postsynaptic voltage i (nA) : current = g*(v - Erev) g (umho) : conductance Rinf : steady state channels open Rtau (ms) : time constant of channel binding synon gmax } STATE {Ron Roff} INITIAL { Rinf = Cmax*Alpha / (Cmax*Alpha + Beta) Rtau = 1 / ((Alpha * Cmax) + Beta) synon = 0 } BREAKPOINT { SOLVE release METHOD cnexp g = (Ron + Roff)*1(umho) i = g*(v - Erev) } DERIVATIVE release { Ron' = (synon*Rinf - Ron)/Rtau Roff' = -Beta*Roff } : following supports both saturation from single input and : summation from multiple inputs : if spike occurs during CDur then new off time is t + CDur : ie. transmitter concatenates but does not summate : Note: automatic initialization of all reference args to 0 except first NET_RECEIVE(weight, on, nspike, r0, t0 (ms)) { : flag is an implicit argument of NET_RECEIVE and normally 0 if (flag == 0) { : a spike, so turn on if not already in a Cdur pulse nspike = nspike + 1 if (!on) { r0 = r0*exp(-Beta*(t - t0)) t0 = t on = 1 synon = synon + weight state_discontinuity(Ron, Ron + r0) state_discontinuity(Roff, Roff - r0) } : come again in Cdur with flag = current value of nspike net_send(Cdur, nspike) } if (flag == nspike) { : if this associated with last spike then turn off r0 = weight*Rinf + (r0 - weight*Rinf)*exp(-(t - t0)/Rtau) t0 = t synon = synon - weight state_discontinuity(Ron, Ron - r0) state_discontinuity(Roff, Roff + r0) on = 0 } gmax=weight }