def cell_description(self, gid):
c = A.cable_cell(self.the_morphology, A.label_dict())
c.set_properties(Vm=0.0, cm=0.01, rL=30, tempK=300)
c.paint('(all)', "pas")
c.place('(location 0 0)', A.iclamp(current=10 if gid == 0 else 20))
c.place('(sum (on-branches 0.3) (location 0 0.6))', "expsyn")
return c
def cell_description(self, gid):
"""A high level description of the cell with global identifier gid.
For example the morphology, synapses and ion channels required
to build a multi-compartment neuron.
"""
assert gid == 0
tree = arbor.segment_tree()
tree.append(arbor.mnpos,
arbor.mpoint(0, 0, 0, self.radius),
arbor.mpoint(self.length, 0, 0, self.radius),
tag=1)
labels = arbor.label_dict({'cable': '(tag 1)',
'start': '(location 0 0)'})
decor = arbor.decor()
decor.set_property(Vm=self.Vm)
decor.set_property(cm=self.cm)
decor.set_property(rL=self.rL)
decor.paint('"cable"',
arbor.density(f'pas/e={self.Vm}', {'g': self.g}))
decor.place('"start"', arbor.iclamp(self.stimulus_start, self.stimulus_duration, self.stimulus_amplitude), "iclamp")
policy = arbor.cv_policy_max_extent(self.cv_policy_max_extent)
decor.discretization(policy)
return arbor.cable_cell(tree, labels, decor)
def test_iclamp(self):
# Constant amplitude iclamp:
clamp = A.iclamp(10)
self.assertEqual(0, clamp.frequency)
self.assertEqual([(0, 10)], clamp.envelope)
clamp = A.iclamp(10, frequency=20)
self.assertEqual(20, clamp.frequency)
self.assertEqual([(0, 10)], clamp.envelope)
# Square pulse:
clamp = A.iclamp(100, 20, 3)
self.assertEqual(0, clamp.frequency)
self.assertEqual([(100, 3), (120, 3), (120, 0)], clamp.envelope)
clamp = A.iclamp(100, 20, 3, frequency=7)
self.assertEqual(7, clamp.frequency)
self.assertEqual([(100, 3), (120, 3), (120, 0)], clamp.envelope)
# Explicit envelope:
envelope = [(1, 10), (3, 30), (5, 50), (7, 0)]
clamp = A.iclamp(envelope)
self.assertEqual(0, clamp.frequency)
self.assertEqual(envelope, clamp.envelope)
clamp = A.iclamp(envelope, frequency=7)
self.assertEqual(7, clamp.frequency)
self.assertEqual(envelope, clamp.envelope)
def __init__(self):
A.recipe.__init__(self)
st = A.segment_tree()
st.append(A.mnpos, (0, 0, 0, 10), (1, 0, 0, 10), 1)
dec = A.decor()
dec.place('(location 0 0.08)', A.synapse("expsyn"), "syn0")
dec.place('(location 0 0.09)', A.synapse("exp2syn"), "syn1")
dec.place('(location 0 0.1)', A.iclamp(20.), "iclamp")
dec.paint('(all)', A.density("hh"))
self.cell = A.cable_cell(st, A.label_dict(), dec)
self.props = A.neuron_cable_properties()
self.props.catalogue = A.default_catalogue()
def make_cable_cell(morphology, clamp_location):
# number of CVs per branch
cvs_per_branch = 3
# Label dictionary
defs = {}
labels = arbor.label_dict(defs)
# decor
decor = arbor.decor()
# set initial voltage, temperature, axial resistivity, membrane capacitance
decor.set_property(
Vm=-65, # Initial membrane voltage (mV)
tempK=300, # Temperature (Kelvin)
rL=10000, # Axial resistivity (Ω cm)
cm=0.01, # Membrane capacitance (F/m**2)
)
# set passive mechanism all over
# passive mech w. leak reversal potential (mV)
pas = arbor.mechanism('pas/e=-65')
pas.set('g', 0.0001) # leak conductivity (S/cm2)
decor.paint('(all)', arbor.density(pas))
# set number of CVs per branch
policy = arbor.cv_policy_fixed_per_branch(cvs_per_branch)
decor.discretization(policy)
# place sinusoid input current
iclamp = arbor.iclamp(
5, # stimulation onset (ms)
1E8, # stimulation duration (ms)
-0.001, # stimulation amplitude (nA)
frequency=0.1, # stimulation frequency (kHz)
phase=0) # stimulation phase)
decor.place(str(clamp_location), iclamp, '"iclamp"')
# create ``arbor.place_pwlin`` object
p = arbor.place_pwlin(morphology)
# create cell and set properties
cell = arbor.cable_cell(morphology, labels, decor)
return p, cell
def cable_cell():
# (1) Create a morphology with a single (cylindrical) segment of length=diameter=6 μm
tree = arbor.segment_tree()
tree.append(
arbor.mnpos,
arbor.mpoint(-3, 0, 0, 3),
arbor.mpoint(3, 0, 0, 3),
tag=1,
)
# (2) Define the soma and its midpoint
labels = arbor.label_dict({'soma': '(tag 1)',
'midpoint': '(location 0 0.5)'})
# (3) Create cell and set properties
decor = arbor.decor()
decor.set_property(Vm=-40)
decor.paint('"soma"', arbor.density('hh'))
decor.place('"midpoint"', arbor.iclamp( 10, 2, 0.8), "iclamp")
decor.place('"midpoint"', arbor.spike_detector(-10), "detector")
return arbor.cable_cell(tree, labels, decor)
def create_arbor_cell(cell, nl_network, gid):
if cell.arbor_cell=='cable_cell':
default_tree = arbor.segment_tree()
radius = evaluate(cell.parameters['radius'], nl_network.parameters) if 'radius' in cell.parameters else 3
default_tree.append(arbor.mnpos, arbor.mpoint(-1*radius, 0, 0, radius), arbor.mpoint(radius, 0, 0, radius), tag=1)
labels = arbor.label_dict({'soma': '(tag 1)',
'center': '(location 0 0.5)'})
labels['root'] = '(root)'
decor = arbor.decor()
v_init = evaluate(cell.parameters['v_init'], nl_network.parameters) if 'v_init' in cell.parameters else -70
decor.set_property(Vm=v_init)
decor.paint('"soma"', cell.parameters['mechanism'])
if gid==0:
ic = arbor.iclamp( nl_network.parameters['input_del'], nl_network.parameters['input_dur'], nl_network.parameters['input_amp'])
print_v("Stim: %s"%ic)
decor.place('"center"', ic)
decor.place('"center"', arbor.spike_detector(-10))
# (2) Mark location for synapse at the midpoint of branch 1 (the first dendrite).
labels['synapse_site'] = '(location 0 0.5)'
# (4) Attach a single synapse.
decor.place('"synapse_site"', 'expsyn')
default_cell = arbor.cable_cell(default_tree, labels, decor)
print_v("Created a new cell for gid %i: %s"%(gid,cell))
print_v("%s"%(default_cell))
return default_cell
def simulate(self, traj):
cell = arb.cable_cell(self.morphology, self.labels)
cell.compartments_length(20)
cell.set_properties(tempK=self.defaults.tempK,
Vm=self.defaults.Vm,
cm=self.defaults.cm,
rL=self.defaults.rL)
for region, vs in self.regions:
cell.paint(f'"{region}"',
tempK=vs.tempK,
Vm=vs.Vm,
cm=vs.cm,
rL=vs.rL)
for region, ion, e in self.ions:
cell.paint(f'"{region}"', ion, rev_pot=e)
cell.set_ion('ca',
int_con=5e-5,
ext_con=2.0,
method=arb.mechanism('nernst/x=ca'))
tmp = defaultdict(dict)
for key, val in traj.individual.items():
region, mech, valuename = key.split('.')
tmp[(region, mech)][valuename] = val
for (region, mech), values in tmp.items():
cell.paint(f'"{region}"', arb.mechanism(mech, values))
cell.place('"center"', arb.iclamp(200, 1000, 0.15))
model = arb.single_cell_model(cell)
model.probe('voltage', '"center"', frequency=200000)
model.properties.catalogue = arb.allen_catalogue()
model.properties.catalogue.extend(arb.default_catalogue(), '')
model.run(tfinal=1400, dt=0.005)
voltages = np.array(model.traces[0].value[:])
return (((voltages - self.reference)**2).sum(), )
# (1) Create a morphology with a single (cylindrical) segment of length=diameter=6 μm
tree = arbor.segment_tree()
tree.append(arbor.mnpos,
arbor.mpoint(-3, 0, 0, 3),
arbor.mpoint(3, 0, 0, 3),
tag=1)
# (2) Define the soma and its midpoint
labels = arbor.label_dict({'soma': '(tag 1)', 'midpoint': '(location 0 0.5)'})
# (3) Create cell and set properties
decor = arbor.decor()
decor.set_property(Vm=-40)
decor.paint('"soma"', 'hh')
decor.place('"midpoint"', arbor.iclamp(10, 2, 0.8))
decor.place('"midpoint"', arbor.spike_detector(-10))
# (4) Create cell and the single cell model based on it
cell = arbor.cable_cell(tree, labels, decor)
# (5) Make single cell model.
m = arbor.single_cell_model(cell)
# (6) Attach voltage probe sampling at 10 kHz (every 0.1 ms).
m.probe('voltage', '"midpoint"', frequency=10000)
# (7) Run simulation for 30 ms of simulated activity.
m.run(tfinal=30)
# (8) Print spike times.
decor = arbor.decor()
# Set initial membrane potential to -55 mV
decor.set_property(Vm=-55)
# Use Nernst to calculate reversal potential for calcium.
decor.set_ion('ca', method=mech('nernst/x=ca'))
#decor.set_ion('ca', method='nernst/x=ca')
# hh mechanism on the soma and axon.
decor.paint('"soma"', 'hh')
decor.paint('"axon"', 'hh')
# pas mechanism the dendrites.
decor.paint('"dend"', 'pas')
# Increase resistivity on dendrites.
decor.paint('"dend"', rL=500)
# Attach stimuli that inject 4 nA current for 1 ms, starting at 3 and 8 ms.
decor.place('"root"', arbor.iclamp(10, 1, current=5), "iclamp0")
decor.place('"stim_site"', arbor.iclamp(3, 1, current=0.5), "iclamp1")
decor.place('"stim_site"', arbor.iclamp(10, 1, current=0.5), "iclamp2")
decor.place('"stim_site"', arbor.iclamp(8, 1, current=4), "iclamp3")
# Detect spikes at the soma with a voltage threshold of -10 mV.
decor.place('"axon_end"', arbor.spike_detector(-10), "detector")
# Create the policy used to discretise the cell into CVs.
# Use a single CV for the soma, and CVs of maximum length 1 μm elsewhere.
soma_policy = arbor.cv_policy_single('"soma"')
dflt_policy = arbor.cv_policy_max_extent(1.0)
policy = dflt_policy | soma_policy
decor.discretization(policy)
# Combine morphology with region and locset definitions to make a cable cell.
cell = arbor.cable_cell(morpho, labels, decor)
decor.set_property(Vm =-55)
# Override the defaults.
decor.paint('"custom"', tempK=270)
decor.paint('"soma"', Vm=-50)
# Paint density mechanisms.
decor.paint('"all"', 'pas')
decor.paint('"custom"', 'hh')
decor.paint('"dend"', mech('Ih', {'gbar': 0.001}))
# Place stimuli and spike detectors.
decor.place('"root"', arbor.iclamp(10, 1, current=2))
decor.place('"root"', arbor.iclamp(30, 1, current=2))
decor.place('"root"', arbor.iclamp(50, 1, current=2))
decor.place('"axon_terminal"', arbor.spike_detector(-10))
# Set cv_policy
soma_policy = arbor.cv_policy_single('"soma"')
dflt_policy = arbor.cv_policy_max_extent(1.0)
policy = dflt_policy | soma_policy
decor.discretization(policy)
# Create a cell
cell = arbor.cable_cell(morph, labels, decor)
print(cell.locations('axon_end'))
# Set initial membrane potential to -55 mV
cell.set_properties(Vm=-55)
# Use Nernst to calculate reversal potential for calcium.
cell.set_ion('ca', method=mech('nernst/x=ca'))
# hh mechanism on the soma and axon.
cell.paint('soma', 'hh')
cell.paint('axon', 'hh')
# pas mechanism the dendrites.
cell.paint('dend', 'pas')
# Increase resistivity on dendrites.
cell.paint('dend', rL=500)
# Attach stimuli that inject 0.8 nA currents for 1 ms, starting at 3 and 8 ms.
cell.place('stim_site', arbor.iclamp(3, 1, current=0.5))
cell.place('stim_site', arbor.iclamp(8, 1, current=1))
# Detect spikes at the soma with a voltage threshold of -10 mV.
cell.place('root', arbor.spike_detector(-10))
# Have one compartment between each sample point.
cell.compartments_on_segments()
# Make single cell model.
m = arbor.single_cell_model(cell)
# Attach voltage probes that sample at 50 kHz.
m.probe('voltage', where='root', frequency=50000)
m.probe('voltage', where=loc(2, 1), frequency=50000)
m.probe('voltage', where='stim_site', frequency=50000)
m.probe('voltage', where='axon_end', frequency=50000)
properties = fit['conditions'][0]
T = properties['celsius'] + 273.15
Vm = properties['v_init']
# Run simulation
ts = []
volts = {}
counts = {}
for i in currents:
morph = arbor.morphology(tree, spherical_root=True)
# Build cell and attach Clamp and Detector
cell = arbor.cable_cell(tree, labels)
#cell.compartments_per_branch(1)
cell.place('center', arbor.iclamp(100, 1000, 0.15))
cell.place('center', arbor.spike_detector(-40))
#cell.set_ion('ca', int_con=5e-5, ext_con=2.0, method=arbor.mechanism('nernst/x=ca'))
cell.set_properties(tempK=T, Vm=Vm, rL=ra)
print(' * Global Parameters')
print(f" * T = {T}K = {T - 273.15}C")
print(f" * Vm = {Vm}mV")
# Set reversal potentials
print(" * Reversal Potential")
for kv in properties['erev']:
region = kv['section']
for k, v in kv.items():
if k == 'section':
continue
'center': '(location 0 0.5)'})
cell = arb.cable_cell(morphology, labels) # see !\circled{3}!
cell.compartments_length(20) # discretisation strategy: max compartment length
# !\circled{4}! load and assign electro-physical parameters
defaults, regions, ions, mechanisms = utils.load_allen_fit('fit.json')
# set defaults and override by region
cell.set_properties(tempK=defaults.tempK, Vm=defaults.Vm,
cm=defaults.cm, rL=defaults.rL)
for region, vs in regions:
cell.paint('"'+region+'"', tempK=vs.tempK, Vm=vs.Vm, cm=vs.cm, rL=vs.rL)
# set reversal potentials
for region, ion, e in ions:
cell.paint('"'+region+'"', ion, rev_pot=e)
cell.set_ion('ca', int_con=5e-5, ext_con=2.0, method=arb.mechanism('nernst/x=ca'))
# assign ion dynamics
for region, mech, values in mechanisms:
cell.paint('"'+region+'"', arb.mechanism(mech, values))
print(mech)
# !\circled{5}! attach stimulus and spike detector
cell.place('"center"', arb.iclamp(200, 1000, 0.15))
cell.place('"center"', arb.spike_detector(-40))
# !\circled{6}! set up runnable simulation
model = arb.single_cell_model(cell)
model.probe('voltage', '"center"', frequency=200000) # see !\circled{5}!
# !\circled{7}! assign catalogues
model.properties.catalogue = arb.allen_catalogue()
model.properties.catalogue.extend(arb.default_catalogue(), '')
# !\circled{8}! run simulation and plot results
model.run(tfinal=1400, dt=0.005)
utils.plot_results(model)
labels['stim_site'] = '(location 0 0.5)' # site for the stimulus
#labels['axon_end'] = '(restrict (terminal) (region "axon_group"))' # end of the axon.
labels[
'dend_end'] = '(restrict (terminal) (region "dendrite_group"))' # end of the axon.
labels[
'root'] = '(root)' # the start of the soma in this morphology is at the root of the cell.
labels['soma'] = '(location 0 0.5)'
#labels['dend1'] = '(location 1 0.5)'
#labels['dend2'] = '(location 2 0.5)'
decor = arbor.decor()
decor.paint('"all"', arbor.mechanism('pas', dict(g=2.01e-05)))
decor.place('"stim_site"', arbor.iclamp(100, 200, 0.1))
# Combine morphology with region and locset definitions to make a cable cell.
cell = arbor.cable_cell(morpho, labels, decor)
print(cell.locations('"dend_end"'))
# Make single cell model.
m = arbor.single_cell_model(cell)
m.probe('voltage', where='"root"', frequency=500)
m.probe('voltage', where='"dend_end"', frequency=500)
# Simulate the cell
print('Simulation start.')
tfinal = 1000 # ms
m.run(tfinal)
# Set the default properties of the cell (this overrides the model defaults).
decor.set_property(Vm=-55)
decor.set_ion('na', int_con=10, ext_con=140, rev_pot=50, method='nernst/na')
decor.set_ion('k', int_con=54.4, ext_con=2.5, rev_pot=-77)
# Override the cell defaults.
decor.paint('"custom"', tempK=270)
decor.paint('"soma"', Vm=-50)
# Paint density mechanisms.
decor.paint('"all"', density('pas'))
decor.paint('"custom"', density('hh'))
decor.paint('"dend"', density('Ih', {'gbar': 0.001}))
# Place stimuli and spike detectors.
decor.place('"root"', arbor.iclamp(10, 1, current=2), 'iclamp0')
decor.place('"root"', arbor.iclamp(30, 1, current=2), 'iclamp1')
decor.place('"root"', arbor.iclamp(50, 1, current=2), 'iclamp2')
decor.place('"axon_terminal"', arbor.spike_detector(-10), 'detector')
# Single CV for the "soma" region
soma_policy = arbor.cv_policy_single('"soma"')
# Single CV for the "soma" region
dflt_policy = arbor.cv_policy_max_extent(1.0)
# default policy everywhere except the soma
policy = dflt_policy | soma_policy
# Set cv_policy
decor.discretization(policy)
# (4) Create the cell.
decor = arbor.decor()
# Set initial membrane potential to -55 mV
decor.set_property(Vm=-55)
# Use Nernst to calculate reversal potential for calcium.
decor.set_ion('ca', method=mech('nernst/x=ca'))
#decor.set_ion('ca', method='nernst/x=ca')
# hh mechanism on the soma and axon.
decor.paint('"soma"', 'hh')
decor.paint('"axon"', 'hh')
# pas mechanism the dendrites.
decor.paint('"dend"', 'pas')
# Increase resistivity on dendrites.
decor.paint('"dend"', rL=500)
# Attach stimuli that inject 4 nA current for 1 ms, starting at 3 and 8 ms.
decor.place('"root"', arbor.iclamp(10, 1, current=5))
decor.place('"stim_site"', arbor.iclamp(3, 1, current=0.5))
decor.place('"stim_site"', arbor.iclamp(10, 1, current=0.5))
decor.place('"stim_site"', arbor.iclamp(8, 1, current=4))
# Detect spikes at the soma with a voltage threshold of -10 mV.
decor.place('"axon_end"', arbor.spike_detector(-10))
# Create the policy used to discretise the cell into CVs.
# Use a single CV for the soma, and CVs of maximum length 1 μm elsewhere.
soma_policy = arbor.cv_policy_single('"soma"')
dflt_policy = arbor.cv_policy_max_extent(1.0)
policy = dflt_policy | soma_policy
decor.discretization(policy)
# Combine morphology with region and locset definitions to make a cable cell.
cell = arbor.cable_cell(morpho, labels, decor)
decor.paint('"all"', 'k_slow')
decor.paint('"all"', 'k_fast')
decor.paint('"all"', 'CaPoolTH')
decor.paint('"all"', 'ca_boyle')
# Set calcium ion concentration.
decor.set_ion('ca', int_con=0, ext_con=2.0, rev_pot = 40.0)
# Set potassium reversal potential
decor.set_ion('k', rev_pot=-60.0)
# Place stimulus and a spike detector.
# Stimulation at the center of the soma from t = 100 ms until t = 400 ms.
# offset current "value"
decor.place('"center"', arbor.iclamp(100, 300, value))
# Spike detection at center of soma.
decor.place('"center"', arbor.spike_detector(-26))
#define CV policy and add it to decor
#policy = arbor.cv_policy_every_segment('(all)')
policy = arbor.cv_policy_fixed_per_branch(1, '(all)')
#policy = arbor.cv_policy_max_extent(1.0)
decor.discretization(policy)
# (4) Create cell.
dd1_cell = arbor.cable_cell(morph, labels, decor)
# (5) Create probes for membrane voltage and calcium ion concentration.
voltage_probe = arbor.cable_probe_membrane_voltage('"center"')
print(cell.locations('"axon_end"'))
# Set initial membrane potential to -55 mV
cell.set_properties(Vm=-55)
# Use Nernst to calculate reversal potential for calcium.
cell.set_ion('ca', method=mech('nernst/x=ca'))
# hh mechanism on the soma and axon.
cell.paint('"soma"', 'hh')
cell.paint('"axon"', 'hh')
# pas mechanism the dendrites.
cell.paint('"dend"', 'pas')
# Increase resistivity on dendrites.
cell.paint('"dend"', rL=500)
# Attach stimuli that inject 0.8 nA currents for 1 ms, starting at 3 and 8 ms.
cell.place('"stim_site"', arbor.iclamp(3, 1, current=2))
cell.place('"stim_site"', arbor.iclamp(8, 1, current=4))
# Detect spikes at the soma with a voltage threshold of -10 mV.
cell.place('"axon_end"', arbor.spike_detector(-10))
# Have one compartment between each sample point.
cell.compartments_on_segments()
# Make single cell model.
m = arbor.single_cell_model(cell)
# Attach voltage probes that sample at 50 kHz.
m.probe('voltage', where='"root"', frequency=50000)
m.probe('voltage', where=loc(2, 1), frequency=50000)
m.probe('voltage', where='"stim_site"', frequency=50000)
m.probe('voltage', where='"axon_end"', frequency=50000)
Vm=-65, # Initial membrane voltage [mV]
tempK=300, # Temperature [Kelvin]
rL=10000, # Axial resistivity [Ω cm]
cm=0.01, # Membrane capacitance [F/m**2]
)
# set passive mechanism all over
# passive mech w. leak reversal potential (mV)
pas = arbor.mechanism('pas/e=-65')
pas.set('g', 0.0001) # leak conductivity (S/cm2)
decor.paint('(all)', arbor.density(pas))
# set sinusoid input current at mid point of terminating CV (segment)
iclamp = arbor.iclamp(
5, # stimulation onset (ms)
1E8, # stimulation duration (ms)
-0.001, # stimulation amplitude (nA)
frequency=0.1, # stimulation frequency (kHz)
phase=0) # stimulation phase)
try:
# arbor >= 0.5.2 fix
decor.place('(location 4 0.16667)', iclamp, '"iclamp"')
except TypeError:
decor.place('(location 4 0.16667)', iclamp)
# number of CVs per branch
policy = arbor.cv_policy_fixed_per_branch(nseg)
decor.discretization(policy)
# create cell and set properties
cell = arbor.cable_cell(morphology, labels, decor)
# (1) Create a morphology with a single (cylindrical) segment of length=diameter=6 μm
tree = arbor.segment_tree()
tree.append(arbor.mnpos,
arbor.mpoint(-3, 0, 0, 3),
arbor.mpoint(3, 0, 0, 3),
tag=1)
# (2) Define the soma and its center
labels = arbor.label_dict({'soma': '(tag 1)', 'center': '(location 0 0.5)'})
# (3) Create cell and set properties
cell = arbor.cable_cell(tree, labels)
cell.set_properties(Vm=-40)
cell.paint('"soma"', 'hh')
cell.place('"center"', arbor.iclamp(10, 2, 0.8))
cell.place('"center"', arbor.spike_detector(-10))
# (4) Make single cell model.
m = arbor.single_cell_model(cell)
# (5) Attach voltage probe sampling at 10 kHz (every 0.1 ms).
m.probe('voltage', '"center"', frequency=10000)
# (6) Run simulation for 30 ms of simulated activity.
m.run(tfinal=30)
# (7) Print spike times, if any.
if len(m.spikes) > 0:
print('{} spikes:'.format(len(m.spikes)))
for s in m.spikes:
import arbor
# Create a sample tree with a single sample of radius 3 μm
tree = arbor.sample_tree()
tree.append(arbor.sample(x=0, y=0, z=0, radius=3, tag=2))
labels = arbor.label_dict({'soma': '(tag 2)', 'center': '(location 0 0.5)'})
cell = arbor.cable_cell(tree, labels)
# Set initial membrane potential everywhere on the cell to -40 mV.
cell.set_properties(Vm=-40)
# Put hh dynamics on soma, and passive properties on the dendrites.
cell.paint('soma', 'hh')
# Attach stimuli with duration of 1 ms and current of 0.8 nA.
cell.place('center', arbor.iclamp( 10, duration=1, current=0.8))
# Add a spike detector with threshold of -10 mV.
cell.place('center', arbor.spike_detector(-10))
# Make single cell model.
m = arbor.single_cell_model(cell)
# Attach voltage probes, sampling at 1 MHz.
m.probe('voltage', 'center', 1000000)
# Run simulation for tfinal ms with time steps of 1 μs.
tfinal=30
m.run(tfinal, dt=0.001)
# Print spike times.
if len(m.spikes)>0:
import arbor
# Create a sample tree with a single sample of radius 3 μm
tree = arbor.sample_tree()
tree.append(arbor.msample(x=0, y=0, z=0, radius=3, tag=2))
labels = arbor.label_dict({'soma': '(tag 2)', 'center': '(location 0 0.5)'})
cell = arbor.cable_cell(tree, labels)
# Set initial membrane potential everywhere on the cell to -40 mV.
cell.set_properties(Vm=-40)
# Put hh dynamics on soma, and passive properties on the dendrites.
cell.paint('soma', 'hh')
# Attach stimuli with duration of 2 ms and current of 0.8 nA.
cell.place('center', arbor.iclamp(10, 2, 0.8))
# Add a spike detector with threshold of -10 mV.
cell.place('center', arbor.spike_detector(-10))
# Make single cell model.
m = arbor.single_cell_model(cell)
# Attach voltage probes, sampling at 10 kHz.
m.probe('voltage', 'center', 10000)
# Run simulation for 100 ms of simulated activity.
tfinal = 30
m.run(tfinal)
# Print spike times.
if len(m.spikes) > 0:
CaPoolTH = arbor.mechanism("CaPoolTH")
# neuroML: <channelDensity id="ca_boyle_all" ionChannel="ca_boyle" condDensity="2 mS_per_cm2" erev="40 mV" ion="ca"/>
ca_boyle_all = arbor.mechanism("ca_boyle")
# put hh dynamics on soma and passive properties on the dendrites
#dd1_cell.paint('"soma"', 'Leak')
dd1_cell.paint('"soma"', 'k_slow')
dd1_cell.paint('"soma"', 'k_fast')
dd1_cell.paint('"soma"', 'CaPoolTH')
dd1_cell.paint('"soma"', 'ca_boyle')
#dd1_cell.paint('"soma"', 'hh')
dd1_cell.place('"center"', arbor.iclamp(100, 300, 0.0087))
dd1_cell.place('"center"', arbor.spike_detector(-26))
# (4) Make single cell model.
m = arbor.single_cell_model(dd1_cell)
# (5) Attach voltage probe sampling at 10 kHz (every 0.1 ms).
m.probe('voltage', '"center"', frequency=10000)
# (6) Run simulation for 30 ms of simulated activity.
m.run(tfinal=500)
# (7) Print spike times, if any.
if len(m.spikes)>0:
print('{} spikes:'.format(len(m.spikes)))
def run_arb(fit, swc, current, t_start, t_stop):
tree = arbor.load_swc_allen(swc, no_gaps=False)
# Load mechanism data
with open(fit) as fd:
fit = json.load(fd)
## collect parameters in dict
mechs = defaultdict(dict)
### Passive parameters
ra = float(fit['passive'][0]['ra'])
### Remaining parameters
for block in fit['genome']:
mech = block['mechanism'] or 'pas'
region = block['section']
name = block['name']
if name.endswith('_' + mech):
name = name[:-(len(mech) + 1)]
mechs[(mech, region)][name] = float(block['value'])
# Label regions
labels = arbor.label_dict({
'soma': '(tag 1)',
'axon': '(tag 2)',
'dend': '(tag 3)',
'apic': '(tag 4)',
'center': '(location 0 0.5)'
})
properties = fit['conditions'][0]
T = properties['celsius'] + 273.15
Vm = properties['v_init']
# Run simulation
morph = arbor.morphology(tree)
# Build cell and attach Clamp and Detector
cell = arbor.cable_cell(morph, labels)
cell.place('center', arbor.iclamp(t_start, t_stop - t_start, current))
cell.place('center', arbor.spike_detector(-40))
cell.compartments_length(20)
# read json file and proceed to set parameters and mechanisms
# set global values
print('Setting global parameters')
print(f" * T = {T}K = {T - 273.15}C")
print(f" * Vm = {Vm}mV")
cell.set_properties(tempK=T, Vm=Vm, rL=ra)
# Set reversal potentials
print("Setting reversal potential for")
for kv in properties['erev']:
region = kv['section']
for k, v in kv.items():
if k == 'section':
continue
ion = k[1:]
print(f' * region {region:6} species {ion:5}: {v:10}')
cell.paint(region, arbor.ion(ion, rev_pot=float(v)))
cell.set_ion('ca',
int_con=5e-5,
ext_con=2.0,
method=arbor.mechanism('default_nernst/x=ca'))
# Setup mechanisms and parameters
print('Setting up mechanisms')
## Now paint the cell using the dict
for (mech, region), vs in mechs.items():
print(f" * {region:10} -> {mech:10}: {str(vs):>60}", end=' ')
try:
if mech != 'pas':
m = arbor.mechanism(mech, vs)
cell.paint(region, m)
else:
m = arbor.mechanism('default_pas', {
'e': vs['e'],
'g': vs['g']
})
cell.paint(region, m)
cell.paint(region, cm=vs["cm"] / 100, rL=vs["Ra"])
print("OK")
except Exception as e:
print("ERROR")
print("When trying to set", mech, vs)
print(" ->", e)
exit()
# Run the simulation, collecting voltages
print('Simulation', end=' ')
default = arbor.default_catalogue()
catalogue = arbor.allen_catalogue()
catalogue.extend(default, 'default_')
model = arbor.single_cell_model(cell)
model.properties.catalogue = catalogue
model.probe('voltage', 'center', frequency=200000)
model.run(tfinal=t_start + t_stop, dt=1000 / 200000)
print('DONE')
for t in model.traces:
ts = t.time[:]
vs = t.value[:]
break
spikes = np.array(model.spikes)
count = len(spikes)
print('Counted spikes', count)
return np.array(ts), np.array(vs) + 14
morph = arbor.morphology(tree, spherical_root=True)
# Label regions
labels = arbor.label_dict({
'soma': '(tag 1)',
'axon': '(tag 2)',
'dend': '(tag 3)',
'apic': '(tag 4)',
'center': '(location 0 0.5)'
})
# Build cell and attach Clamp and Detector
cell = arbor.cable_cell(tree, labels)
cell.place('center', arbor.iclamp(200, 1200, i))
cell.place('center', arbor.spike_detector(-40))
# read json file and proceed to set parameters and mechanisms
with open('473561729/473561729_fit.json') as fd:
fit = json.load(fd)
# set global values
print('Setting global parameters')
properties = fit['conditions'][0]
T = properties['celsius'] + 273.15
print(f" * T = {T}K = {T - 273.15}C")
Vm = properties['v_init']
print(f" * Vm = {Vm}mV")
cell.set_properties(tempK=T, Vm=Vm, rL=ra)
b.add_label('dtips', '(terminal)')
# Extract the cable cell from the builder.
cell = b.build()
# Set initial membrane potential everywhere on the cell to -40 mV.
cell.set_properties(Vm=-40)
# Put hh dynamics on soma, and passive properties on the dendrites.
cell.paint('soma', 'hh')
cell.paint('dend', 'pas')
# Set axial resistivity in dendrite regions (Ohm.cm)
cell.paint('dendn', rL=500)
cell.paint('dendx', rL=10000)
# Attach stimuli with duration of 2 ms and current of 0.8 nA.
# There are three stimuli, which activate at 10 ms, 50 ms and 80 ms.
cell.place('stim_site', arbor.iclamp(10, 2, 0.8))
cell.place('stim_site', arbor.iclamp(50, 2, 0.8))
cell.place('stim_site', arbor.iclamp(80, 2, 0.8))
# Add a spike detector with threshold of -10 mV.
cell.place('root', arbor.spike_detector(-10))
# Make single cell model.
m = arbor.single_cell_model(cell)
# Attach voltage probes, sampling at 10 kHz.
m.probe('voltage', loc(0, 0), 10000) # at the soma.
m.probe('voltage', 'dtips', 10000) # at the tips of the dendrites.
# Run simulation for 100 ms of simulated activity.
tfinal = 100
m.run(tfinal)
def create_arbor_cell(self, cell, gid, pop_id, index):
if cell.arbor_cell == "cable_cell":
default_tree = arbor.segment_tree()
radius = (evaluate(cell.parameters["radius"],
self.nl_network.parameters)
if "radius" in cell.parameters else 3)
default_tree.append(
arbor.mnpos,
arbor.mpoint(-1 * radius, 0, 0, radius),
arbor.mpoint(radius, 0, 0, radius),
tag=1,
)
labels = arbor.label_dict({
"soma": "(tag 1)",
"center": "(location 0 0.5)"
})
labels["root"] = "(root)"
decor = arbor.decor()
v_init = (evaluate(cell.parameters["v_init"],
self.nl_network.parameters)
if "v_init" in cell.parameters else -70)
decor.set_property(Vm=v_init)
decor.paint('"soma"', arbor.density(cell.parameters["mechanism"]))
decor.place('"center"', arbor.spike_detector(0), "detector")
for ip in self.input_info:
if self.input_info[ip][0] == pop_id:
print_v("Stim: %s (%s) being placed on %s" %
(ip, self.input_info[ip], pop_id))
for il in self.input_lists[ip]:
cellId, segId, fract, weight = il
if cellId == index:
if self.input_info[ip][
1] == 'i_clamp': # TODO: remove hardcoding of this...
ic = arbor.iclamp(
self.nl_network.parameters["input_del"],
self.nl_network.parameters["input_dur"],
self.nl_network.parameters["input_amp"],
)
print_v("Stim: %s on %s" % (ic, gid))
decor.place('"center"', ic, "iclamp")
# (2) Mark location for synapse at the midpoint of branch 1 (the first dendrite).
labels["synapse_site"] = "(location 0 0.5)"
# (4) Attach a single synapse.
decor.place('"synapse_site"', arbor.synapse("expsyn"), "syn")
default_cell = arbor.cable_cell(default_tree, labels, decor)
print_v("Created a new cell for gid %i: %s" % (gid, cell))
print_v("%s" % (default_cell))
return default_cell
decor.set_property(Vm=-55)
# Override the defaults.
decor.paint('"custom"', tempK=270)
decor.paint('"soma"', Vm=-50)
# Paint density mechanisms.
decor.paint('"all"', 'pas')
decor.paint('"custom"', 'hh')
decor.paint('"dend"', mech('Ih', {'gbar': 0.001}))
# Place stimuli and spike detectors.
decor.place('"root"', arbor.iclamp(10, 1, current=2), "iclamp0")
decor.place('"root"', arbor.iclamp(30, 1, current=2), "iclamp1")
decor.place('"root"', arbor.iclamp(50, 1, current=2), "iclamp2")
decor.place('"axon_terminal"', arbor.spike_detector(-10), "detector")
# Set cv_policy
soma_policy = arbor.cv_policy_single('"soma"')
dflt_policy = arbor.cv_policy_max_extent(1.0)
policy = dflt_policy | soma_policy
decor.discretization(policy)
# Create a cell
cell = arbor.cable_cell(morph, labels, decor)
# Morphology
tree = arbor.segment_tree()
tree.append(arbor.mnpos,
arbor.mpoint(-3, 0, 0, 3),
arbor.mpoint(3, 0, 0, 3),
tag=1)
# Label dictionary
labels = arbor.label_dict()
labels['centre'] = '(location 0 0.5)'
# Decorations
decor = arbor.decor()
decor.set_property(Vm=-40)
decor.paint('(all)', 'hh')
decor.place('"centre"', arbor.iclamp(10, 2, 0.8))
decor.place('"centre"', arbor.spike_detector(-10))
cell = arbor.cable_cell(tree, labels, decor)
# (3) Instantiate recipe with a voltage probe.
recipe = single_recipe(cell, [arbor.cable_probe_membrane_voltage('"centre"')])
# (4) Instantiate simulation and set up sampling on probe id (0, 0).
context = arbor.context()
domains = arbor.partition_load_balance(recipe, context)
sim = arbor.simulation(recipe, domains, context)
sim.record(arbor.spike_recording.all)
