:Pyramidal Cells to Interneuron Cells AMPA+NMDA with local Ca2+ pool NEURON { POINT_PROCESS pyrD2interV_STFD USEION ca READ eca NONSPECIFIC_CURRENT inmda, iampa RANGE initW RANGE Cdur_nmda, AlphaTmax_nmda, Beta_nmda, Erev_nmda, gbar_nmda, W_nmda, on_nmda, g_nmda RANGE Cdur_ampa, AlphaTmax_ampa, Beta_ampa, Erev_ampa, gbar_ampa, W, on_ampa, g_ampa RANGE eca, ICan, P0n, fCan, tauCa, Icatotal RANGE ICaa, P0a, fCaa RANGE Cainf, pooldiam, z RANGE lambda1, lambda2, threshold1, threshold2 RANGE fmax, fmin, Wmax, Wmin, maxChange, normW, scaleW, srcid, destid RANGE pregid,postgid, thr_rp RANGE F, f, tauF, D1, d1, tauD1, D2, d2, tauD2 RANGE facfactor } UNITS { (mV) = (millivolt) (nA) = (nanoamp) (uS) = (microsiemens) FARADAY = 96485 (coul) pi = 3.141592 (1) } PARAMETER { srcid = -1 (1) destid = -1 (1) Cdur_nmda = 16.7650 (ms) AlphaTmax_nmda = .2659 (/ms) Beta_nmda = 0.008 (/ms) Erev_nmda = 0 (mV) gbar_nmda = .5e-3 (uS) Cdur_ampa = 0.713 (ms) AlphaTmax_ampa = 10.1571 (/ms) Beta_ampa = 0.4167 (/ms) Erev_ampa = 0 (mV) gbar_ampa = 1e-3 (uS) eca = 120 Cainf = 50e-6 (mM) pooldiam = 1.8172 (micrometer) z = 2 tauCa = 50 (ms) P0n = .015 fCan = .024 P0a = .001 fCaa = .024 lambda1 = 3 lambda2 = .01 threshold1 = 0.35 : 0.4 : 0.45 :0.5 (uM) threshold2 = 0.4 : 0.45 : 0.5 :0.6 (uM) :AMPA Weight initW = 1.5 :3 :1.5 :1 fmax = 3 : 2 fmin = .8 thr_rp = 1 : .7 facfactor = 1 : the (1) is needed for the range limits to be effective f = 1 (1) < 0, 1e9 > : facilitation : 1.3 (1) < 0, 1e9 > : facilitation tauF = 45 (ms) < 1e-9, 1e9 > d1 = 0.95 (1) < 0, 1 >: 0.95 (1) < 0, 1 > : fast depression tauD1 = 40 (ms) < 1e-9, 1e9 > d2 = 0.9 (1) < 0, 1 > : 0.9 (1) < 0, 1 > : slow depression tauD2 = 70 (ms) < 1e-9, 1e9 > } ASSIGNED { v (mV) inmda (nA) g_nmda (uS) on_nmda W_nmda iampa (nA) g_ampa (uS) on_ampa W t0 (ms) ICan (mA) ICaa (mA) Afactor (mM/ms/nA) Icatotal (mA) dW_ampa Wmax Wmin maxChange normW scaleW pregid postgid rp tsyn fa F D1 D2 } STATE { r_nmda r_ampa capoolcon } INITIAL { on_nmda = 0 r_nmda = 0 W_nmda = initW on_ampa = 0 r_ampa = 0 W = initW t0 = -1 Wmax = fmax*initW Wmin = fmin*initW maxChange = (Wmax-Wmin)/10 dW_ampa = 0 capoolcon = Cainf Afactor = 1/(z*FARADAY*4/3*pi*(pooldiam/2)^3)*(1e6) fa =0 F = 1 D1 = 1 D2 = 1 } BREAKPOINT { SOLVE release METHOD cnexp } DERIVATIVE release { if (t0>0) { if (rp < thr_rp) { if (t-t0 < Cdur_nmda) { on_nmda = 1 } else { on_nmda = 0 } if (t-t0 < Cdur_ampa) { on_ampa = 1 } else { on_ampa = 0 } } else { on_nmda = 0 on_ampa = 0 } } r_nmda' = AlphaTmax_nmda*on_nmda*(1-r_nmda)-Beta_nmda*r_nmda r_ampa' = AlphaTmax_ampa*on_ampa*(1-r_ampa)-Beta_ampa*r_ampa dW_ampa = eta(capoolcon)*(lambda1*omega(capoolcon, threshold1, threshold2)-lambda2*W)*dt : Limit for extreme large weight changes if (fabs(dW_ampa) > maxChange) { if (dW_ampa < 0) { dW_ampa = -1*maxChange } else { dW_ampa = maxChange } } :Normalize the weight change normW = (W-Wmin)/(Wmax-Wmin) if (dW_ampa < 0) { scaleW = sqrt(fabs(normW)) } else { scaleW = sqrt(fabs(1.0-normW)) } W = W + dW_ampa*scaleW :Weight value limits if (W > Wmax) { W = Wmax } else if (W < Wmin) { W = Wmin } g_nmda = gbar_nmda*r_nmda*facfactor inmda = W_nmda*g_nmda*(v - Erev_nmda)*sfunc(v) g_ampa = gbar_ampa*r_ampa*facfactor iampa = W*g_ampa*(v - Erev_ampa) ICan = P0n*g_nmda*(v - eca)*sfunc(v) ICaa = P0a*W*g_ampa*(v-eca)/initW Icatotal = ICan + ICaa capoolcon'= -fCan*Afactor*Icatotal + (Cainf-capoolcon)/tauCa } NET_RECEIVE(dummy_weight) { t0 = t rp = unirand() :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) ::printf("%g\t%g\t%g\t%g\n", F, D1, D2, facfactor) tsyn = t facfactor = F * D1 * D2 F = F * f if (F > 2) { F=2 } if (facfactor < 0.7) { facfactor=0.7 } if (F < 0.8) { F=0.8 } D1 = D1 * d1 D2 = D2 * d2 :printf("\t%g\t%g\t%g\n", F, D1, D2) } :::::::::::: FUNCTIONs and PROCEDUREs :::::::::::: FUNCTION sfunc (v (mV)) { UNITSOFF sfunc = 1/(1+0.33*exp(-0.06*v)) UNITSON } 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 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))} } FUNCTION unirand() { : uniform random numbers between 0 and 1 unirand = scop_random() }