def __init__(self, **parameters):
# define ion channel parameters
leak = Mechanism('pas', e=-65, g=parameters['g_leak'])
hh = Mechanism('hh',
gl=parameters['g_leak'],
el=-65,
gnabar=parameters['gnabar'],
gkbar=parameters['gkbar'])
# create cable sections
self.soma = Section(L=30, diam=30, mechanisms=[hh])
self.apical = Section(L=600,
diam=2,
nseg=5,
mechanisms=[leak],
parent=self.soma,
connect_to=1)
self.basilar = Section(L=600,
diam=2,
nseg=5,
mechanisms=[leak],
parent=self.soma)
self.axon = Section(L=1000, diam=1, nseg=37, mechanisms=[hh])
# synaptic input
self.apical.add_synapse('ampa', 'Exp2Syn', e=0.0, tau1=0.1, tau2=5.0)
# needed for PyNN
self.source_section = self.soma
self.source = self.soma(0.5)._ref_v
self.parameter_names = ('g_leak', 'gnabar', 'gkbar')
self.traces = {}
self.recording_time = False
def __init__(self, **parameters):
# Create single compartment Rubin and Terman GP cell section, i.e. soma section
self.soma = Section(L=parameters['L'],
diam=parameters['diam'],
nseg=parameters['nseg'],
Ra=parameters['Ra'],
cm=parameters['cm'],
mechanisms=[
Mechanism('myions'),
Mechanism('GPeA',
gnabar=0.04,
gkdrbar=0.0042,
gkcabar=0.1e-3,
gcatbar=6.7e-5,
kca=2,
gl=4e-5)
])
# Initialize ion concentrations
h("cai0_ca_ion = 5e-6 ")
h("cao0_ca_ion = 2")
h("ki0_k_ion = 105")
h("ko0_k_ion = 3")
h("nao0_na_ion = 108")
h("nai0_na_ion = 10")
# insert current source
self.stim = h.IClamp(0.5, sec=self.soma)
self.stim.delay = 0
self.stim.dur = 1e12
self.stim.amp = parameters['bias_current']
# Add DBS stimulation current to neuron model
self.DBS_stim = h.IClamp(0.5, sec=self.soma)
self.DBS_stim.delay = 0
self.DBS_stim.dur = 1e9
self.DBS_stim.amp = 0
# Append the DBS stimulation iclamps to global list
GV.GPe_stimulation_iclamps.append(self.DBS_stim)
# Add AMPA and GABAa synapses to the cell, i.e. add to the soma section
self.AMPA = h.AMPA_S(0.5, sec=self.soma)
self.GABAa = h.GABAa_S(0.5, sec=self.soma)
# needed for PyNN
self.source_section = self.soma
self.source = self.soma(0.5)._ref_v
self.rec = h.NetCon(self.source, None,
sec=self.soma) # Needed to clear the simulator
self.spike_times = h.Vector(0)
self.parameter_names = ('L', 'diam', 'nseg', 'Ra', 'cm',
'bias_current_density')
self.traces = {}
self.recording_time = False
def insert_mechanism(self, mech):
"""
Insert density mechanism into cell
:param mech:
"""
if isinstance(mech, basestring):
mech = Mechanism(mech)
mech.insert_into(self.soma)
self.setRevVar()
self.setConc()
def create_mechanisms(self, g_na_bar=2000, g_k_bar=5, g_im_bar=0.00012,
g_pas_k=0.000125, p_na=0.23, p_cl=0.4,
**kwargs):
g_pas_na = g_pas_k * p_na
g_pas_cl = g_pas_k * p_cl
# mechanisms
self.na = Mechanism('na', gbar=g_na_bar)
self.kv = Mechanism('kv', gbar=g_k_bar)
self.im = Mechanism('im', gkbar=g_im_bar)
self.pasghk = Mechanism('pasghk', gclpbar=g_pas_cl, gnapbar=g_pas_na, gkpbar=g_pas_k)
self.mechanisms.append(self.na)
self.mechanisms.append(self.kv)
self.mechanisms.append(self.im)
self.mechanisms.append(self.pasghk)
def __init__(self, **parameters):
# Create single compartment Otsuka STN cell section, i.e. soma section
self.soma = Section(L=parameters['L'],
diam=parameters['diam'],
nseg=parameters['nseg'],
Ra=parameters['Ra'],
cm=parameters['cm'],
mechanisms=[
Mechanism('myions'),
Mechanism('stn',
gnabar=49e-3,
gkdrbar=57e-3,
gkabar=5e-3,
gkcabar=1.0e-3,
gcalbar=15e-3,
gcatbar=5e-3,
kca=2,
gl=0.35e-3)
])
# Initialize ion concentrations
h("cai0_ca_ion = 5e-6 ")
h("cao0_ca_ion = 2")
h("ki0_k_ion = 105")
h("ko0_k_ion = 3")
h("nao0_na_ion = 108")
h("nai0_na_ion = 10")
# Add bias current to neuron model
self.stim = h.IClamp(0.5, sec=self.soma)
self.stim.delay = 0
self.stim.dur = 1e12
self.stim.amp = parameters['bias_current'] # bias current density (nA)
# Add AMPA and GABAa synapses to the cell, i.e. add to the soma section
self.AMPA = h.AMPA_S(0.5, sec=self.soma)
self.GABAa = h.GABAa_S(0.5, sec=self.soma)
# needed for PyNN
self.source_section = self.soma
self.source = self.soma(0.5)._ref_v
self.rec = h.NetCon(self.source, None,
sec=self.soma) # Needed to clear the simulator
self.spike_times = h.Vector(0)
self.parameter_names = ('L', 'diam', 'nseg', 'Ra', 'cm',
'bias_current')
self.traces = {}
self.recording_time = False
def __init__(self,
ion_type,
current_type,
L=20,
diam=20,
Ra=150,
g_pas=0.00003334):
self.ion_type = ion_type
self.current_type = current_type
leak = Mechanism('pas', e=-65, g=g_pas)
self.soma = Section(L, diam, Ra=Ra, mechanisms=[leak])
def __init__(self, **parameters):
# Create single compartment Rubin and Terman Thalamic cell section, i.e. soma section
self.soma = Section(L=parameters['L'],
diam=parameters['diam'],
nseg=parameters['nseg'],
Ra=parameters['Ra'],
cm=parameters['cm'],
mechanisms=(Mechanism('thalamic_i_leak'),
Mechanism('thalamic_i_na_k'),
Mechanism('thalamic_i_t')))
"""
# Note: Thalamic current has no bias current in original paper, i.e. bias_current_density = 0
# Can be added in if required.
# insert current source
self.stim = h.IClamp(0.5, sec=self.soma)
self.stim.delay = 0
self.stim.dur = 1e12
self.stim.amp = parameters['bias_current_density']*(self.area())*(0.001) # (0.001 or 1e-3) is conversion factor so pA -> nA
"""
# insert synaptic noise
self.noise = h.SynNoise(0.5, sec=self.soma)
self.noise.f0 = 0
self.noise.f1 = 0.3
# Add AMPA and GABAa synapses to the cell, i.e. add to the soma section
self.AMPA = h.AMPA_S(0.5, sec=self.soma)
self.GABAa = h.GABAa_S(0.5, sec=self.soma)
# needed for PyNN
self.source_section = self.soma
self.source = self.soma(0.5)._ref_v
self.rec = h.NetCon(self.source, None,
sec=self.soma) # Needed to clear the simulator
self.spike_times = h.Vector(0)
self.parameter_names = ('L', 'diam', 'nseg', 'Ra', 'cm',
'bias_current_density')
self.traces = {}
self.recording_time = False
def __init__(self, **parameters):
# Create single compartment Destexhe Interneuron cell section, i.e. soma section
self.soma = Section(L=parameters['L'],
diam=parameters['diam'],
nseg=parameters['nseg'],
Ra=parameters['Ra'],
cm=parameters['cm'],
mechanisms=(Mechanism('interneuron_i_leak'),
Mechanism('interneuron_i_na'),
Mechanism('interneuron_i_k')))
# Add bias current to neuron model - current amplitude is in terms of original model paper, nA
self.stim = h.IClamp(0.5, sec=self.soma)
self.stim.delay = 0
self.stim.dur = 1e12
self.stim.amp = parameters['bias_current_amp'] # nA
# insert synaptic noise
self.noise = h.SynNoise(0.5, sec=self.soma)
self.noise.f0 = 0
self.noise.f1 = 0.3
# Add AMPA and GABAa synapses to the cell, i.e. add to the soma section
self.AMPA = h.AMPA_S(0.5, sec=self.soma)
self.GABAa = h.GABAa_S(0.5, sec=self.soma)
# needed for PyNN
self.source_section = self.soma
self.source = self.soma(0.5)._ref_v
self.rec = h.NetCon(
self.source, None,
sec=self.source_section) # Needed to clear the simulator
self.spike_times = h.Vector(0)
self.parameter_names = ('L', 'diam', 'nseg', 'Ra', 'cm',
'bias_current_amp')
self.traces = {}
self.recording_time = False
def without_ih():
# Model with standard potassium und sodium currents
model = AxonWithBoutons(axon_mechanisms=[
Mechanism('nax', gbar=nax_axon),
Mechanism('Kv1', gbar=Kv1_axon),
Mechanism('leakNa', g=leakNa_axon),
Mechanism('leakK', g=leakK_axon),
],
bouton_mechanisms=[
Mechanism('nax', gbar=nax_bouton),
Mechanism('Kv1', gbar=Kv1_bouton),
Mechanism('leakNa', g=leakNa_bouton),
Mechanism('leakK', g=leakK_bouton),
],
all_ena=myena,
all_ek=myek)
return model
def create_mechanisms(self,**kwargs):
Rm = 20000 # Ohm cm^2 membrane resistance
self.pas = Mechanism('pas', e=-65, g=(1.0 / Rm))
assert self.pas.parameters['g'] > 0, "division not working correctly"
self.mechanisms.append(self.pas)
def __init__(self, **parameters):
# Create cortical pyramidal neuron soma compartment using Pospischil (2008) single compartment model
self.soma = Section(L=parameters['soma_L'],
diam=parameters['soma_diam'],
nseg=parameters['soma_nseg'],
Ra=parameters['soma_Ra'],
cm=parameters['soma_cm'],
mechanisms=(Mechanism('cortical_soma_i_leak'),
Mechanism('cortical_soma_i_na'),
Mechanism('cortical_soma_i_k'),
Mechanism('cortical_soma_i_m')))
# Create cortical pyramidal neuron axon compartments using Foust (2011) axon model
self.ais = Section(L=parameters['ais_L'],
diam=parameters['ais_diam'],
nseg=parameters['ais_nseg'],
Ra=parameters['ais_Ra'],
cm=parameters['ais_cm'],
mechanisms=(Mechanism('cortical_axon_i_leak',
g_l=3.3e-5),
Mechanism('cortical_axon_i_na',
g_Na=4000e-4),
Mechanism('cortical_axon_i_kv',
g_Kv=20e-4),
Mechanism('cortical_axon_i_kd',
g_Kd=0.015)),
parent=self.soma)
# Use loop to create myelin and node sections of axon
self.myelin = []
self.node = []
for i in np.arange(parameters['num_axon_compartments']):
if i == 0:
self.myelin.append(
Section(L=parameters['myelin_L'],
diam=parameters['myelin_diam'],
nseg=11,
Ra=parameters['myelin_Ra'],
cm=parameters['myelin_cm'],
mechanisms=(Mechanism('cortical_axon_i_leak',
g_l=0),
Mechanism('cortical_axon_i_na',
g_Na=10e-4)),
parent=self.ais))
else:
self.myelin.append(
Section(L=parameters['myelin_L'],
diam=parameters['myelin_diam'],
nseg=11,
Ra=parameters['myelin_Ra'],
cm=parameters['myelin_cm'],
mechanisms=(Mechanism('cortical_axon_i_leak',
g_l=0),
Mechanism('cortical_axon_i_na',
g_Na=10e-4)),
parent=self.node[i - 1]))
self.node.append(
Section(L=parameters['node_L'],
diam=parameters['node_diam'],
nseg=parameters['node_nseg'],
Ra=parameters['node_Ra'],
cm=parameters['node_cm'],
mechanisms=(Mechanism('cortical_axon_i_leak',
g_l=0.02),
Mechanism('cortical_axon_i_na',
g_Na=2800e-4),
Mechanism('cortical_axon_i_kv', g_Kv=5e-4),
Mechanism('cortical_axon_i_kd',
g_Kd=0.0072)),
parent=self.myelin[i]))
self.collateral = Section(
L=parameters['collateral_L'],
diam=parameters['collateral_diam'],
nseg=parameters['collateral_nseg'],
Ra=parameters['collateral_Ra'],
cm=parameters['collateral_cm'],
mechanisms=(Mechanism('cortical_axon_i_leak'),
Mechanism('cortical_axon_i_na', g_Na=1333.33333e-4),
Mechanism('cortical_axon_i_kv', g_Kv=10e-4),
Mechanism('cortical_axon_i_kd', g_Kd=0.006)),
parent=self.node[-1])
middle_index = int((parameters['num_axon_compartments'] / 2.0))
self.middle_node = self.node[middle_index]
self.middle_myelin = self.myelin[middle_index]
# Add extracellular and xtra mechanisms to collateral
self.collateral.insert('extracellular')
self.collateral.insert('xtra')
# Assign default rx values to the segments rx_xtra
# - these values are updated in the main run file
# where rx is calculated as the transfer resistance
# for each collateral segments to the stimulation
# electrode in the homogenous extracellular medium
for seg in self.collateral:
seg.xtra.rx = seg.x * 3e-1
# Setting pointers to couple extracellular and xtra mechanisms for simulating extracellular DBS
for seg in self.collateral:
h.setpointer(seg._ref_e_extracellular, 'ex', seg.xtra)
h.setpointer(seg._ref_i_membrane, 'im', seg.xtra)
# Add bias current to neuron model - current amplitude is in terms of original model paper, nA
self.stim = h.IClamp(0.5, sec=self.soma)
self.stim.delay = 0
self.stim.dur = 1e12
self.stim.amp = parameters['soma_bias_current_amp']
# insert synaptic noise
self.noise = h.SynNoise(0.5, sec=self.soma)
self.noise.f0 = 0
self.noise.f1 = 0.3
# Add AMPA and GABAa synapses to the cell, i.e. add to the soma section
self.AMPA = h.AMPA_S(0.5, sec=self.soma)
self.GABAa = h.GABAa_S(0.5, sec=self.soma)
# needed for PyNN
self.source = {
'soma': self.soma(0.5)._ref_v,
'middle_axon_node': self.middle_node(0.5)._ref_v,
'collateral': self.collateral(0.5)._ref_v
}
self.source_section = {
'soma': self.soma,
'middle_axon_node': self.middle_node,
'collateral': self.collateral
}
self.rec = h.NetCon(self.source['collateral'],
None,
sec=self.source_section['collateral']
) # Needed to clear the simulator
self.spike_times = h.Vector(0)
self.traces = {}
self.recording_time = False
self.parameter_names = ()
def add_kcc2(self, **kwargs):
kcc2 = Mechanism('KCC2', **kwargs)
for section in self.sections:
kcc2.insert_into(section)
self.kcc2_inserted = True
return self
