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 __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, **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 __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 = ()