import matplotlib.pyplot as plt
import numpy as np
from brian2 import *
from brian_models import *
start_scope()
# False: Figure 7B
# True: Figure 7C
adp = True
v_th = 30
if adp:
a = 1
b = 0.2
c = 60
d = 15
ta = TimedArray([0,1,1,0], dt=5*ms)
ta2 = TimedArray([0,1,1,1,1,0], dt=5*ms)
Izhikevich_eqs = Izhikevich_eqs + '''
I = 0. + 5.*(ta(t200./4*ms)
+ ta2(t400./4*ms)
+ 1.5*ta(t600./4*ms)
+ 1.5*ta2(t800./4*ms)): 1'''
else:
a = 0.5
b = 0.6
c = 65
d = 6
ta = TimedArray([0,1,1,0], dt=5*ms)
ta2 = TimedArray([0,1,1,1,1,0], dt=5*ms)
Izhikevich_eqs = Izhikevich_eqs + '''
I = 20. + 5.*(ta(t200./4*ms)
+ ta2(t400./4*ms)
+ 1.5*ta(t600./4*ms)
+ 1.5*ta2(t800./4*ms)): 1'''
G = NeuronGroup(1, Izhikevich_eqs, threshold = Izhikevich_threshold, reset = Izhikevich_reset, dt=0.1*ms, method='rk4')
M = StateMonitor(G, ['v','I'], record=0)
spikemon = SpikeMonitor(G)
G.v = 70.0
G.u = 70.0*0.2
run(250*ms)
t = M.t/ms
V = M[0].v
V = (Vmin(V))/(max(V)min(V))*100.
I = M[0].I
I = 105.+(Imin(I))/(max(I)min(I))*10.
# Draw spikes
for ti in spikemon.t:
i = int(ti / G.dt)
V[i] = 100.
# Plot
plt.figure()
plt.plot(t, V, t, I)
plt.show()
