nmdadyn = ''' dNMDAoS/dt = (1/t_Nr)*(Nnor*NMDAi-NMDAoS) : 1 dNMDAi/dt = -(1/t_Nf)*NMDAi : 1 Nnor = (t_Nf/t_Nr)**((t_Nr)/(t_Nf - t_Nr)) : 1 Nscal = (t_Nf/msecond)**(t_Nf/(t_Nf - t_Nr))/(t_Nr/msecond)**(t_Nr/(t_Nf - t_Nr)) : 1 NMDAo = NMDAoS / Nscal : 1 w : 1 # synaptic weight ''' s_eq = SynapticEquations(nmdadyn+ampadyn,**params) S=Synapses(input,neurons, model=s_eq, pre='NMDAi+=w\nAMPAi+=w',post='',clock=simclock) # NMDA synapses neurons.NMDAo=S.NMDAo neurons.AMPAo=S.AMPAo S[:,:]=True S.w=[0.01,0.01] S.delay=[0.003,0.005] input.v=[0.,0.5] M=StateMonitor(S,'NMDAo',record=True,clock=simclock) M0 = StateMonitor(S,'NMDAi',record=True,clock=simclock) M2=StateMonitor(S,'AMPAo',record=True,clock=simclock) Mn=StateMonitor(neurons,'v',record=True,clock=simclock) run(100*ms) subplot(411) plot(M0.times/ms,M0[0]) plot(M0.times/ms,M0[1]) subplot(412)