def create_cell(cell_id):
# type: (str) -> Cell
"""Create a NeuroML Cell.
Initialises the cell with these properties assigning IDs where applicable:
- Morphology: "morphology"
- BiophysicalProperties: "biophys"
- MembraneProperties
- IntracellularProperties
- SegmentGroups: "all", "soma_group", "dendrite_group", "axon_group" which
can be used to include all, soma, dendrite, and axon segments
respectively.
Note that since this cell does not currently include a segment in its
morphology, it is *not* a valid NeuroML construct. Use the `add_segment`
function to add segments. `add_segment` will also populate the default
segment groups this creates.
:param cell_id: id of the cell
:type cell_id: str
:returns: created cell object of type neuroml.Cell
"""
cell = Cell(id=cell_id)
cell.morphology = Morphology(id='morphology')
membrane_properties = MembraneProperties()
intracellular_properties = IntracellularProperties()
cell.biophysical_properties = BiophysicalProperties(
id="biophys",
intracellular_properties=intracellular_properties,
membrane_properties=membrane_properties)
seg_group_all = SegmentGroup(id='all')
seg_group_soma = SegmentGroup(
id='soma_group',
neuro_lex_id=neuro_lex_ids["soma"],
notes="Default soma segment group for the cell")
seg_group_axon = SegmentGroup(
id='axon_group',
neuro_lex_id=neuro_lex_ids["axon"],
notes="Default axon segment group for the cell")
seg_group_dend = SegmentGroup(
id='dendrite_group',
neuro_lex_id=neuro_lex_ids["dend"],
notes="Default dendrite segment group for the cell")
cell.morphology.segment_groups.append(seg_group_all)
cell.morphology.segment_groups.append(seg_group_soma)
cell.morphology.segment_groups.append(seg_group_axon)
cell.morphology.segment_groups.append(seg_group_dend)
return cell
def create_generic_neuron_cell(self):
self.generic_neuron_cell = Cell(id="GenericNeuronCell")
morphology = Morphology()
morphology.id = "morphology_" + self.generic_neuron_cell.id
self.generic_neuron_cell.morphology = morphology
prox_point = Point3DWithDiam(
x="0",
y="0",
z="0",
diameter=self.get_bioparameter("cell_diameter").value)
dist_point = Point3DWithDiam(
x="0",
y="0",
z="0",
diameter=self.get_bioparameter("cell_diameter").value)
segment = Segment(id="0",
name="soma",
proximal=prox_point,
distal=dist_point)
morphology.segments.append(segment)
self.generic_neuron_cell.biophysical_properties = BiophysicalProperties(
id="biophys_" + self.generic_neuron_cell.id)
mp = MembraneProperties()
self.generic_neuron_cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(
InitMembPotential(
value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(
SpecificCapacitance(value=self.get_bioparameter(
"neuron_specific_capacitance").value))
mp.spike_threshes.append(
SpikeThresh(
value=self.get_bioparameter("neuron_spike_thresh").value))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
'''
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("neuron_k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))'''
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_ca_simple_cond_density").value,
id="ca_simple_all",
ion_channel="ca_simple",
erev=self.get_bioparameter("ca_simple_erev").value,
ion="ca"))
ip = IntracellularProperties()
self.generic_neuron_cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(Resistivity(value="0.1 kohm_cm"))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
def create_models(self):
self.generic_cell = Cell(id = "GenericCell")
morphology = Morphology()
morphology.id = "morphology_"+self.generic_cell.id
self.generic_cell.morphology = morphology
prox_point = Point3DWithDiam(x="0", y="0", z="0", diameter=self.get_bioparameter("cell_diameter").value)
dist_point = Point3DWithDiam(x="0", y="0", z=self.get_bioparameter("cell_length").value, diameter=self.get_bioparameter("cell_diameter").value)
segment = Segment(id="0",
name="soma",
proximal = prox_point,
distal = dist_point)
morphology.segments.append(segment)
self.generic_cell.biophysical_properties = BiophysicalProperties(id="biophys_"+self.generic_cell.id)
mp = MembraneProperties()
self.generic_cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(InitMembPotential(value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(SpecificCapacitance(value=self.get_bioparameter("specific_capacitance").value))
mp.spike_threshes.append(SpikeThresh(value=self.get_bioparameter("spike_thresh").value))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))
mp.channel_densities.append(ChannelDensity(cond_density=self.get_bioparameter("ca_boyle_cond_density").value,
id="ca_boyle_all",
ion_channel="ca_boyle",
erev=self.get_bioparameter("ca_boyle_erev").value,
ion="ca"))
ip = IntracellularProperties()
self.generic_cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(Resistivity(value="0.1 kohm_cm"))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
self.exc_syn = GradedSynapse(id="exc_syn",
conductance = self.get_bioparameter("exc_syn_conductance").value,
delta = self.get_bioparameter("exc_syn_delta").value,
Vth = self.get_bioparameter("exc_syn_vth").value,
erev = self.get_bioparameter("exc_syn_erev").value,
k = self.get_bioparameter("exc_syn_k").value)
self.inh_syn = GradedSynapse(id="inh_syn",
conductance = self.get_bioparameter("inh_syn_conductance").value,
delta = self.get_bioparameter("inh_syn_delta").value,
Vth = self.get_bioparameter("inh_syn_vth").value,
erev = self.get_bioparameter("inh_syn_erev").value,
k = self.get_bioparameter("inh_syn_k").value)
self.elec_syn = GapJunction(id="elec_syn",
conductance = self.get_bioparameter("elec_syn_gbase").value)
self.offset_current = PulseGenerator(id="offset_current",
delay=self.get_bioparameter("unphysiological_offset_current_del").value,
duration=self.get_bioparameter("unphysiological_offset_current_dur").value,
amplitude=self.get_bioparameter("unphysiological_offset_current").value)
def create_cell():
"""Create the cell.
:returns: name of the cell nml file
"""
# Create the nml file and add the ion channels
hh_cell_doc = NeuroMLDocument(id="cell", notes="HH cell")
hh_cell_fn = "HH_example_cell.nml"
hh_cell_doc.includes.append(IncludeType(href=create_na_channel()))
hh_cell_doc.includes.append(IncludeType(href=create_k_channel()))
hh_cell_doc.includes.append(IncludeType(href=create_leak_channel()))
# Define a cell
hh_cell = Cell(id="hh_cell", notes="A single compartment HH cell")
# Define its biophysical properties
bio_prop = BiophysicalProperties(id="hh_b_prop")
# notes="Biophysical properties for HH cell")
# Membrane properties are a type of biophysical properties
mem_prop = MembraneProperties()
# Add membrane properties to the biophysical properties
bio_prop.membrane_properties = mem_prop
# Append to cell
hh_cell.biophysical_properties = bio_prop
# Channel density for Na channel
na_channel_density = ChannelDensity(id="na_channels", cond_density="120.0 mS_per_cm2", erev="50.0 mV", ion="na", ion_channel="na_channel")
mem_prop.channel_densities.append(na_channel_density)
# Channel density for k channel
k_channel_density = ChannelDensity(id="k_channels", cond_density="360 S_per_m2", erev="-77mV", ion="k", ion_channel="k_channel")
mem_prop.channel_densities.append(k_channel_density)
# Leak channel
leak_channel_density = ChannelDensity(id="leak_channels", cond_density="3.0 S_per_m2", erev="-54.3mV", ion="non_specific", ion_channel="leak_channel")
mem_prop.channel_densities.append(leak_channel_density)
# Other membrane properties
mem_prop.spike_threshes.append(SpikeThresh(value="-20mV"))
mem_prop.specific_capacitances.append(SpecificCapacitance(value="1.0 uF_per_cm2"))
mem_prop.init_memb_potentials.append(InitMembPotential(value="-65mV"))
intra_prop = IntracellularProperties()
intra_prop.resistivities.append(Resistivity(value="0.03 kohm_cm"))
# Add to biological properties
bio_prop.intracellular_properties = intra_prop
# Morphology
morph = Morphology(id="hh_cell_morph")
# notes="Simple morphology for the HH cell")
seg = Segment(id="0", name="soma", notes="Soma segment")
# We want a diameter such that area is 1000 micro meter^2
# surface area of a sphere is 4pi r^2 = 4pi diam^2
diam = math.sqrt(1000 / math.pi)
proximal = distal = Point3DWithDiam(x="0", y="0", z="0", diameter=str(diam))
seg.proximal = proximal
seg.distal = distal
morph.segments.append(seg)
hh_cell.morphology = morph
hh_cell_doc.cells.append(hh_cell)
pynml.write_neuroml2_file(nml2_doc=hh_cell_doc, nml2_file_name=hh_cell_fn, validate=True)
return hh_cell_fn
def create_neuron_cell(self, cell_name, morphology):
cell = Cell(id=cell_name)
cell.notes = "Cell model created by c302 with custom electrical parameters"
cell.morphology = morphology
cell.biophysical_properties = BiophysicalProperties(id="biophys_" +
cell.id)
mp = MembraneProperties()
cell.biophysical_properties.membrane_properties = mp
mp.init_memb_potentials.append(
InitMembPotential(
value=self.get_bioparameter("initial_memb_pot").value))
mp.specific_capacitances.append(
SpecificCapacitance(
value=self.get_bioparameter("specific_capacitance").value))
mp.spike_threshes.append(
SpikeThresh(
value=self.get_bioparameter("neuron_spike_thresh").value))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_leak_cond_density").value,
id="Leak_all",
ion_channel="Leak",
erev=self.get_bioparameter("leak_erev").value,
ion="non_specific"))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_k_slow_cond_density").value,
id="k_slow_all",
ion_channel="k_slow",
erev=self.get_bioparameter("k_slow_erev").value,
ion="k"))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_k_fast_cond_density").value,
id="k_fast_all",
ion_channel="k_fast",
erev=self.get_bioparameter("k_fast_erev").value,
ion="k"))
mp.channel_densities.append(
ChannelDensity(cond_density=self.get_bioparameter(
"neuron_ca_boyle_cond_density").value,
id="ca_boyle_all",
ion_channel="ca_boyle",
erev=self.get_bioparameter("ca_boyle_erev").value,
ion="ca"))
ip = IntracellularProperties()
cell.biophysical_properties.intracellular_properties = ip
# NOTE: resistivity/axial resistance not used for single compartment cell models, so value irrelevant!
ip.resistivities.append(
Resistivity(value=self.get_bioparameter("resistivity").value))
# NOTE: Ca reversal potential not calculated by Nernst, so initial_ext_concentration value irrelevant!
species = Species(id="ca",
ion="ca",
concentration_model="CaPool",
initial_concentration="0 mM",
initial_ext_concentration="2E-6 mol_per_cm3")
ip.species.append(species)
return cell