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 cell_description(self, gid):
tree = arbor.segment_tree()
tree.append(arbor.mnpos,
arbor.mpoint(-3, 0, 0, 3),
arbor.mpoint(3, 0, 0, 3),
tag=1)
labels = arbor.label_dict({
'soma': '(tag 1)',
'center': '(location 0 0.5)'
})
decor = arbor.decor()
decor.set_property(Vm=-40)
decor.paint('(all)', arbor.density('hh'))
decor.place('"center"', arbor.spike_detector(-10), "detector")
decor.place('"center"', arbor.synapse('expsyn'), "synapse")
mech = arbor.mechanism('expsyn_stdp')
mech.set("max_weight", 1.)
syn = arbor.synapse(mech)
decor.place('"center"', syn, "stpd_synapse")
cell = arbor.cable_cell(tree, labels, decor)
return cell
def cell_description(self, gid):
tree = arb.segment_tree()
tree.append(arb.mnpos,
arb.mpoint(-3, 0, 0, 3),
arb.mpoint(3, 0, 0, 3),
tag=1)
decor = arb.decor()
decor.place('(location 0 0.5)', arb.gap_junction_site(), "gj")
return arb.cable_cell(tree, arb.label_dict(), decor)
def cable_cell(cls, morphology=0, decor=None, labels=None):
try:
import arbor
except ImportError:
raise ImportError("`arbor` unavailable, can't make arbor models.")
morph, labels, decor = cls.cable_cell_template(morphology, decor,
labels)
return arbor.cable_cell(morph, labels, decor)
def make_cable_cell(gid):
# (1) Build a segment tree
tree = arbor.segment_tree()
# Soma (tag=1) with radius 6 μm, modelled as cylinder of length 2*radius
s = tree.append(arbor.mnpos,
arbor.mpoint(-12, 0, 0, 6),
arbor.mpoint(0, 0, 0, 6),
tag=1)
# Single dendrite (tag=3) of length 50 μm and radius 2 μm attached to soma.
b0 = tree.append(s,
arbor.mpoint(0, 0, 0, 2),
arbor.mpoint(50, 0, 0, 2),
tag=3)
# Attach two dendrites (tag=3) of length 50 μm to the end of the first dendrite.
# Radius tapers from 2 to 0.5 μm over the length of the dendrite.
b1 = tree.append(b0,
arbor.mpoint(50, 0, 0, 2),
arbor.mpoint(50 + 50 / sqrt(2), 50 / sqrt(2), 0, 0.5),
tag=3)
# Constant radius of 1 μm over the length of the dendrite.
b2 = tree.append(b0,
arbor.mpoint(50, 0, 0, 1),
arbor.mpoint(50 + 50 / sqrt(2), -50 / sqrt(2), 0, 1),
tag=3)
# Associate labels to tags
labels = arbor.label_dict()
labels['soma'] = '(tag 1)'
labels['dend'] = '(tag 3)'
# (2) Mark location for synapse at the midpoint of branch 1 (the first dendrite).
labels['synapse_site'] = '(location 1 0.5)'
labels['synapse_site2'] = '(location 1 0.5)'
# Mark the root of the tree.
labels['root'] = '(root)'
# (3) Create a decor and a cable_cell
decor = arbor.decor()
# Put hh dynamics on soma, and passive properties on the dendrites.
decor.paint('"soma"', 'hh')
decor.paint('"dend"', 'pas')
# (4) Attach a single synapse.
decor.place('"synapse_site"', 'expsyn')
decor.place('"synapse_site2"', 'expsyn')
# Attach a spike detector with threshold of -10 mV.
decor.place('"root"', arbor.spike_detector(-10))
cell = arbor.cable_cell(tree, labels, decor)
return cell
def __init__(self):
arb.recipe.__init__(self)
self.tree = arb.segment_tree()
self.tree.append(arb.mnpos, (0, 0, 0, 10), (1, 0, 0, 10), 1)
self.props = arb.neuron_cable_properties()
self.props.catalogue = arb.load_catalogue(cat)
d = arb.decor()
d.paint('(all)', 'dummy')
d.set_property(Vm=0.0)
self.cell = arb.cable_cell(self.tree, arb.label_dict(), d)
def make_cable_cell(gid):
# (1) Build a segment tree
# https://docs.arbor-sim.org/en/latest/concepts/morphology.html
tree = arbor.segment_tree()
# Soma (tag=1) with radius 6 μm, modelled as cylinder of length 2*radius
s = tree.append(arbor.mnpos,
arbor.mpoint(-12, 0, 0, 6),
arbor.mpoint(0, 0, 0, 6),
tag=1)
# Single dendrite (tag=3) of length 50 μm and radius 2 μm attached to soma.
b0 = tree.append(s,
arbor.mpoint(0, 0, 0, 2),
arbor.mpoint(50, 0, 0, 2),
tag=3)
# Attach two dendrites (tag=3) of length 50 μm to the end of the first dendrite.
# Radius tapers from 2 to 0.5 μm over the length of the dendrite.
b1 = TODO
# Constant radius of 1 μm over the length of the dendrite.
b2 = TODO
# Associate labels to tags
# https://docs.arbor-sim.org/en/latest/concepts/labels.html
labels = arbor.label_dict()
labels['soma'] = '(tag 1)'
labels['dend'] = '(tag 3)'
# (2) Mark location for synapse at the midpoint of branch 1 (the first dendrite).
# https://docs.arbor-sim.org/en/latest/concepts/labels.html
labels['synapse_site'] = TODO
# Mark the root of the tree.
labels['root'] = TODO
# (3) Create a decor and a cable_cell
# https://docs.arbor-sim.org/en/latest/python/decor.html
decor = arbor.decor()
# Put hh dynamics on soma, and passive properties on the dendrites.
decor.paint('"soma"', 'hh')
decor.paint('"dend"', 'pas')
# (4) Attach a single synapse.
decor.place('"synapse_site"', 'expsyn', 'syn')
# Attach a spike detector with threshold of -10 mV.
decor.place(TODO)
cell = arbor.cable_cell(tree, labels, decor)
return cell
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)', "expsyn")
dec.place('(location 0 0.09)', "exp2syn")
dec.paint('(all)', "hh")
self.cell = A.cable_cell(st, A.label_dict(), dec)
self.cat = A.default_catalogue()
self.props = A.neuron_cable_propetries()
self.props.register(self.cat)
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 __init__(self):
arb.recipe.__init__(self)
self.tree = arb.segment_tree()
self.tree.append(arb.mnpos, (0, 0, 0, 10), (1, 0, 0, 10), 1)
self.props = arb.neuron_cable_properties()
try:
self.cat = arb.default_catalogue()
self.props.register(self.cat)
except:
print("Catalogue not found. Are you running from build directory?")
raise
d = arb.decor()
d.paint('(all)', arb.density('pas'))
d.set_property(Vm=0.0)
self.cell = arb.cable_cell(self.tree, arb.label_dict(), d)
def make_cable_cell(gid):
# Build a segment tree
tree = arbor.segment_tree()
# Soma with radius 5 μm and length 2 * radius = 10 μm, (tag = 1)
s = tree.append(arbor.mnpos,
arbor.mpoint(-10, 0, 0, 5),
arbor.mpoint(0, 0, 0, 5),
tag=1)
# Single dendrite with radius 2 μm and length 40 μm, (tag = 2)
b = tree.append(s,
arbor.mpoint(0, 0, 0, 2),
arbor.mpoint(40, 0, 0, 2),
tag=2)
# Label dictionary for cell components
labels = arbor.label_dict()
labels['soma'] = '(tag 1)'
labels['dend'] = '(tag 2)'
# Mark location for synapse site at midpoint of dendrite (branch 0 = soma + dendrite)
labels['synapse_site'] = '(location 0 0.6)'
# Gap junction site at connection point of soma and dendrite
labels['gj_site'] = '(location 0 0.2)'
# Label root of the tree
labels['root'] = '(root)'
# Paint dynamics onto the cell, hh on soma and passive properties on dendrite
decor = arbor.decor()
decor.paint('"soma"', arbor.density("hh"))
decor.paint('"dend"', arbor.density("pas"))
# Attach one synapse and gap junction each on their labeled sites
decor.place('"synapse_site"', arbor.synapse('expsyn'), 'syn')
decor.place('"gj_site"', arbor.junction('gj'), 'gj')
# Attach spike detector to cell root
decor.place('"root"', arbor.spike_detector(-10), 'detector')
cell = arbor.cable_cell(tree, labels, decor)
return cell
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 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 in [0, 1]
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({
'cell': '(tag 1)',
'gj_site': '(location 0 0.5)'
})
decor = arbor.decor()
decor.set_property(Vm=self.Vms[gid])
decor.set_property(cm=self.cm)
decor.set_property(rL=self.rL)
# add a gap junction mechanism at the "gj_site" location and label that specific mechanism on that location "gj_label"
junction_mech = arbor.junction('gj', {"g": self.gj_g})
decor.place('"gj_site"', junction_mech, 'gj_label')
decor.paint('"cell"',
arbor.density(f'pas/e={self.Vms[gid]}', {'g': self.g}))
if self.cv_policy_max_extent is not None:
policy = arbor.cv_policy_max_extent(self.cv_policy_max_extent)
decor.discretization(policy)
else:
decor.discretization(arbor.cv_policy_single())
return arbor.cable_cell(tree, labels, decor)
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(), )
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)
# (2) Declare a probe.
probe = arbor.cable_probe_membrane_voltage('"custom_terminal"')
# (3) Create a recipe class and instantiate a recipe
class single_recipe(arbor.recipe):
def __init__(self, cell, probes):
# The base C++ class constructor must be called first, to ensure that
# all memory in the C++ class is initialized correctly.
arbor.recipe.__init__(self)
self.the_cell = cell
self.the_probes = probes
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:
# Associate labels to tags
labels = arbor.label_dict()
labels['soma'] = '(tag 0)'
labels['axon'] = '(tag 1)'
labels['dend_2'] = '(tag 2)'
labels['neur_3'] = '(tag 3)'
labels['neur_4'] = '(tag 4)'
labels['center'] = '(location 0 0.5)'
# create dd1 morphology
morph = arbor.morphology(tree)
# create cell
dd1_cell = arbor.cable_cell(morph, labels)
# neuroML: <specificCapacitance value="1 uF_per_cm2"/>, <initMembPotential value="-45 mV"/>, <resistivity value="12 kohm_cm"/>
# set cable properties
# Vm = initial membrane potential (-45 mV)
# cm = membrane capacitance (0.01 F / m²)
# rL = axial resistivity of cable (12000 Ohm * cm)
# tempK = temperature in Kelvin (not provided by c302)
dd1_cell.set_properties(Vm = -45, cm = 0.01, rL = 12000)
#cat = arbor.default_catalogue()
# define dynamics / mechanisms
# neuroML: <channelDensity id="Leak_all" ionChannel="Leak" condDensity="0.02 mS_per_cm2" erev="-50 mV" ion="non_specific"/>
Leak = arbor.mechanism("Leak")
import utils, arbor as arb
# !\circled{1}! read in geometry
segment_tree = arb.load_swc_allen('cell.swc', no_gaps=False)
morphology = arb.morphology(segment_tree)
# !\circled{2}! assign names to regions defined by SWC and center of soma
labels = arb.label_dict({'soma': '(tag 1)', 'axon': '(tag 2)',
'dend': '(tag 3)', 'apic': '(tag 4)',
'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)
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.
if len(m.spikes) > 0:
print('{} spikes:'.format(len(m.spikes)))
for s in m.spikes:
print('{:3.3f}'.format(s))
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)
# create single cell model
model = arbor.single_cell_model(cell)
# instantiate recipe with cell
recipe = Recipe(cell)
# instantiate simulation
context = arbor.context()
domains = arbor.partition_load_balance(recipe, context)
sim = arbor.simulation(recipe, domains, context)
# set up sampling on probes
schedule = arbor.regular_schedule(0.1)
v_handle = sim.sample(recipe.vprobe_id, schedule, arbor.sampling_policy.exact)
'uniform0': '(uniform (tag 3) 0 9 0)',
'uniform1': '(uniform (tag 3) 0 9 1)',
'branchmid': '(on-branches 0.5)',
'distal': '(distal (region "rad36"))',
'proximal':'(proximal (region "rad36"))',
'distint_in': '(sum (location 1 0.5) (location 2 0.7) (location 5 0.1))',
'proxint_in': '(sum (location 1 0.8) (location 2 0.3))',
'loctest' : '(distal (complete (join (branch 1) (branch 0))))',
'restrict': '(restrict (terminal) (tag 3))',
}
labels = {**regions, **locsets}
d = arbor.label_dict(labels)
# Create a cell to concretise the region and locset definitions
cell = arbor.cable_cell(label_morph, d, arbor.decor())
###############################################################################
# Tutorial Example: single_cell_detailed
###############################################################################
tree = arbor.segment_tree()
tree.append(mnpos, mpoint(0, 0.0, 0, 2.0), mpoint( 4, 0.0, 0, 2.0), tag=1)
tree.append(0, mpoint(4, 0.0, 0, 0.8), mpoint( 8, 0.0, 0, 0.8), tag=3)
tree.append(1, mpoint(8, 0.0, 0, 0.8), mpoint(12, -0.5, 0, 0.8), tag=3)
tree.append(2, mpoint(12, -0.5, 0, 0.8), mpoint(20, 4.0, 0, 0.4), tag=3)
tree.append(3, mpoint(20, 4.0, 0, 0.4), mpoint(26, 6.0, 0, 0.2), tag=3)
tree.append(2, mpoint(12, -0.5, 0, 0.5), mpoint(19, -3.0, 0, 0.5), tag=3)
tree.append(5, mpoint(19, -3.0, 0, 0.5), mpoint(24, -7.0, 0, 0.2), tag=4)
tree.append(5, mpoint(19, -3.0, 0, 0.5), mpoint(23, -1.0, 0, 0.2), tag=4)
tree.append(7, mpoint(23, -1.0, 0, 0.2), mpoint(36, -2.0, 0, 0.2), tag=4)
'uniform0': '(uniform (tag 3) 0 9 0)',
'uniform1': '(uniform (tag 3) 0 9 1)',
'branchmid': '(on-branches 0.5)',
'distal': '(distal (region "rad36"))',
'proximal': '(proximal (region "rad36"))',
'distint_in': '(sum (location 1 0.5) (location 2 0.7) (location 5 0.1))',
'proxint_in': '(sum (location 1 0.8) (location 2 0.3))',
'loctest': '(distal (complete (join (branch 1) (branch 0))))',
'restrict': '(restrict (terminal) (tag 3))',
}
labels = {**regions, **locsets}
d = arbor.label_dict(labels)
# Create a cell to concretise the region and locset definitions
cell = arbor.cable_cell(label_morph, d, arbor.decor())
###############################################################################
# Tutorial Example
###############################################################################
tree = arbor.segment_tree()
tree.append(mnpos, mpoint(0, 0.0, 0, 2.0), mpoint(4, 0.0, 0, 2.0), tag=1)
tree.append(0, mpoint(4, 0.0, 0, 0.8), mpoint(8, 0.0, 0, 0.8), tag=3)
tree.append(1, mpoint(8, 0.0, 0, 0.8), mpoint(12, -0.5, 0, 0.8), tag=3)
tree.append(2, mpoint(12, -0.5, 0, 0.8), mpoint(20, 4.0, 0, 0.4), tag=3)
tree.append(3, mpoint(20, 4.0, 0, 0.4), mpoint(26, 6.0, 0, 0.2), tag=3)
tree.append(2, mpoint(12, -0.5, 0, 0.5), mpoint(19, -3.0, 0, 0.5), tag=3)
tree.append(5, mpoint(19, -3.0, 0, 0.5), mpoint(24, -7.0, 0, 0.2), tag=4)
tree.append(5, mpoint(19, -3.0, 0, 0.5), mpoint(23, -1.0, 0, 0.2), tag=4)
tree.append(7, mpoint(23, -1.0, 0, 0.2), mpoint(36, -2.0, 0, 0.2), tag=4)
'uniform0': '(uniform (tag 3) 0 9 0)',
'uniform1': '(uniform (tag 3) 0 9 1)',
'branchmid': '(on-branches 0.5)',
'distal': '(distal (region "rad36"))',
'proximal': '(proximal (region "rad36"))',
'distint_in': '(sum (location 1 0.5) (location 2 0.7) (location 5 0.1))',
'proxint_in': '(sum (location 1 0.8) (location 2 0.3))',
'loctest': '(distal (complete (join (branch 1) (branch 0))))',
'restrict': '(restrict (terminal) (tag 3))',
}
labels = {**regions, **locsets}
d = arbor.label_dict(labels)
# Create a cell to concretise the region and locset definitions
cell = arbor.cable_cell(label_morph, d)
################################################################################
# Output all of the morphologies and reion/locset definitions to a Python script
# that can be run during the documentation build to generate images.
################################################################################
f = open('inputs.py', 'w')
f.write('import representation\n')
f.write('from representation import Segment\n')
f.write('\n############# morphologies\n\n')
f.write(write_morphology('label_morph', label_morph))
f.write(write_morphology('detached_morph', detached_morph))
f.write(write_morphology('stacked_morph', stacked_morph))
f.write(write_morphology('sphere_morph', sphere_morph))
f.write(write_morphology('branch_morph1', branch_morph1))
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
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
