subplot(211)
plot(mon_L.t/ms,mon_soma[0].v/mV,"k")
plot(mon_L.t/ms,mon_L[49].v/mV,"r")
plot(mon_L.t/ms,mon_R[49].v/mV,"b")
subplot(212)
for i in [0,5,10,15,20,25,30,35,40,45]:
After Change
// Morphology
morpho=Soma(30*um)
morpho.L=Cylinder(diameter=1*um,length=100*um,n=50)
morpho.R=Cylinder(diameter=1*um,length=100*um,n=50)
// Passive channels
gL = 1e-4*siemens/cm**2
EL = -70*mV
Es = 0*mV
taus = 1*ms
eqs="""
Im = gL*(EL-v)+gs*(Es-v)/area : amp/meter**2
dgs/dt = -gs/taus : siemens
"""
neuron = SpatialNeuron(morphology=morpho, model=eqs, Cm=1 * uF / cm ** 2, Ri=100 * ohm * cm)
neuron.v = EL
// Regular inputs
stimulation = NeuronGroup(2,model="dx/dt=300*Hz : 1",threshold="x>1",reset="x=0")
stimulation.x = [0,0.5] // Asynchronous
// Synapses
w = 20*nS
S = Synapses(stimulation,neuron,pre = "gs += w")
// Here we need a method that gives indices (compartment numbers) or spatial indexing
S.connect(0,morpho.L.compartment(100*um))
S.connect(1,morpho.R.compartment(100*um))
// Monitors
mon_soma=StateMonitor(neuron,"v",record=[0])
mon_L=StateMonitor(neuron.L,"v",record=True)
mon_R=StateMonitor(neuron.R,"v",record=morpho.R.compartment(100*um, local = True))
run(50*ms,report="text")
subplot(211)
plot(mon_L.t/ms,mon_soma[0].v/mV,"k")
plot(mon_L.t/ms,mon_L[morpho.L.compartment(100*um, local = True)].v/mV,"r")
plot(mon_L.t/ms,mon_R[morpho.R.compartment(100*um, local = True)].v/mV,"b")
subplot(212)
for i in [0,5,10,15,20,25,30,35,40,45]:
plot(mon_L.t/ms,mon_L.v[i,:]/mV)
