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)
