def create_cell(self):
self.dummy = h.Section()
cell = h.Izhi2003a(0.5, sec=self.dummy)
for var in self.PARAM_NAMES:
setattr(cell, var, getattr(self, var))
return cell
def __init__ (self, type='tonic spiking', host=None, cellid=-1):
self.type=type
if host is None: # need to set up a sec for this
self.sec=h.Section(name='izhi2003'+type+str(cellid))
self.sec.L, self.sec.diam = 6.3, 5 # empirically tuned
self.izh = h.Izhi2003b(0.5, sec=self.sec)
else:
self.sec = dummy
self.izh = h.Izhi2003a(0.5, sec=self.sec) # Create a new u,V 2007 neuron at location 0.5 (doesn't matter where)
self.izh.a,self.izh.b,self.izh.c,self.izh.d = type2003[type]
self.izh.Iin = 509.7
('subthreshold oscillations' , (0.05 , 0.26 , -60.0 , 0.0 , -62.0 , 200.0)) ,
('rebound burst' , (0.03 , 0.25 , -52.0 , 0.0 , -64.0 , 200.0)) ,
('accomodation' , (0.02 , 1.0 , -55.0 , 4.0 , -65.0 , 400.0)) ,
('tonic bursting' , (0.02 , 0.2 , -50.0 , 2.0 , -70.0 , 220.0)) ,
('Class 1' , (0.02 , -0.1 , -55.0 , 6.0 , -60.0 , 300.0)) ,
('resonator' , (0.1 , 0.26 , -60.0 , -1.0 , -62.0 , 400.0)) ,
('threshold variability' , (0.03 , 0.25 , -60.0 , 4.0 , -64.0 , 100.0)) ,
('inhibition-induced spiking' , (-0.02 , -1.0 , -60.0 , 8.0 , -63.8 , 350.0)) ,
('phasic bursting' , (0.02 , 0.25 , -55.0 , 0.05 , -64.0 , 200.0)) ,
('Class 2' , (0.2 , 0.26 , -65.0 , 0.0 , -64.0 , 300.0)) ,
('integrator' , (0.02 , -0.1 , -55.0 , 6.0 , -60.0 , 100.0)) ,
('bistability' , (0.1 , 0.26 , -60.0 , 0.0 , -61.0 , 300.0)) ,
('inhibition-induced bursting' , (-0.026 , -1.0 , -45.0 , -2.0 , -63.8 , 350.0))])
choices = collections.OrderedDict([
('2003 PP model' , (lambda: h.Izhi2003a(0.5,sec=cell03), lambda: izh._ref_V, type2003)),
('2003 Sec model', (lambda: h.Izhi2003b(0.5,sec=cell03), lambda: cell03(0.5)._ref_v, type2003)),
('2004 PP model' , (lambda: h.Izhi2003a(0.5,sec=cell03), lambda: izh._ref_V, type2004)),
('2004 Sec model', (lambda: h.Izhi2003b(0.5,sec=cell03), lambda: cell03(0.5)._ref_v, type2004)),
('2007 PP model' , (lambda: izh07.IzhiCell(host=izh07.dummy), lambda: izh._ref_V, izh07.type2007)),
('2007 Sec model' , (lambda: izh07.IzhiCell(), lambda: cell07.sec(0.5)._ref_v, izh07.type2007))])
ch=choices.keys()
def newmodel (ty=None) :
"2003,2004 was the orig model; 2007 is the redesign; look at global izhtype if no "
return izhtype.find('2007') > -1 if ty is None else ty.find('2007') > -1
#* setup the cell
izhtype='2004 PP model'
def cellset ():
global cell07, cell03, izh, vref, uvvset, fih, izhtype
# exec(open('Izhitemplate.py').read())
# Author: Anal Kumar, NCBS
# Makes an Izhikevich model (2003a version), inserts GABAR and AMPAR (with modified Exp2Syn mod files),
# one input which connects to AMPAR, and one which connects to GABAR.
# As the in-built Exp2Syn and IClamp mechanisms use the cell's i and v, I have used POINTER so that they use the V and I used in Izhikevich mechanism.
from neuron import h, gui
import numpy as np
import matplotlib.pyplot as plt
v_init = -70
dummyE1 = h.Section(name='dummyE1') #dummy section to insert Izhikevich
izhiE1 = h.Izhi2003a(0.5, sec=dummyE1) #insert Izhikevich
izhiE1.V = v_init
AMPAR = h.Exp2SynAMPAR(dummyE1(0.5)) #insert AMPAR synapse
AMPAR.tau1 = 3.5
AMPAR.tau2 = 21
AMPAR.e = 0
GABAR = h.Exp2SynGABAR(dummyE1(0.5)) #insert GABAR synapse
GABAR.tau1 = 6.4
GABAR.tau2 = 40
GABAR.e = -80
stim = h.IClampizhi(dummyE1(0.5)) #insert IClamp izhikevich version
stim.delay = 1500
stim.dur = 500
can graph u, v for any model
simple.show('v3a','v3b') # compare voltage output for the 2 versions of the 2003/2004 parameterization; will NOT be identical
simple.show('v7a','v7b','v7bw') # compare voltage output for 3 versions of the 2007 parameterization
'''
from neuron import h, gui
import numpy as np
import izhi2007Wrapper as izh07
import pylab as plt
import pprint as pp
plt.ion()
fih = []
dummy = h.Section()
# make a 2003a STATE {u,vv} cell (used for 2003, 2004)
iz03a = h.Izhi2003a(0.5, sec=dummy)
iz03a.Iin = 4
# make a 2003b (Section v) cell
sec03b = h.Section() # this section will actually be used
sec03b.L, sec03b.diam = 5, 6.3 # empirically tuned
iz03b = h.Izhi2003b(0.5, sec=sec03b)
iz03b.Iin = 4
def iz03b_init():
sec03b(0.5).v, iz03b.u = -65, -65 * iz03b.b
fih.append(h.FInitializeHandler(iz03b_init))
('rebound burst', (0.03, 0.25, -52.0, 0.0, -64.0, 200.0)),
('accomodation', (0.02, 1.0, -55.0, 4.0, -65.0, 400.0)),
('tonic bursting', (0.02, 0.2, -50.0, 2.0, -70.0, 220.0)),
('Class 1', (0.02, -0.1, -55.0, 6.0, -60.0, 300.0)),
('resonator', (0.1, 0.26, -60.0, -1.0, -62.0, 400.0)),
('threshold variability', (0.03, 0.25, -60.0, 4.0, -64.0, 100.0)),
('inhibition-induced spiking', (-0.02, -1.0, -60.0, 8.0, -63.8, 350.0)),
('phasic bursting', (0.02, 0.25, -55.0, 0.05, -64.0, 200.0)),
('Class 2', (0.2, 0.26, -65.0, 0.0, -64.0, 300.0)),
('integrator', (0.02, -0.1, -55.0, 6.0, -60.0, 100.0)),
('bistability', (0.1, 0.26, -60.0, 0.0, -61.0, 300.0)),
('inhibition-induced bursting', (-0.026, -1.0, -45.0, -2.0, -63.8, 350.0))
])
choices = collections.OrderedDict([
('2003 PP model', (lambda: h.Izhi2003a(0.5, sec=cell03),
lambda: izh._ref_V, type2003)),
('2003 Sec model', (lambda: h.Izhi2003b(0.5, sec=cell03),
lambda: cell03(0.5)._ref_v, type2003)),
('2004 PP model', (lambda: h.Izhi2003a(0.5, sec=cell03),
lambda: izh._ref_V, type2004)),
('2004 Sec model', (lambda: h.Izhi2003b(0.5, sec=cell03),
lambda: cell03(0.5)._ref_v, type2004)),
('2007 PP model', (lambda: izh07.IzhiCell(host=izh07.dummy),
lambda: izh._ref_V, izh07.type2007)),
('2007 Sec model', (lambda: izh07.IzhiCell(),
lambda: cell07.sec(0.5)._ref_v, izh07.type2007))
])
ch = choices.keys()
