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 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(), )
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 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.mechanism(f'pas/e={self.Vm}', {'g': self.g}))
decor.place(
'"start"',
arbor.iclamp(args.stimulus_start, args.stimulus_duration,
args.stimulus_amplitude), "iclamp")
policy = arbor.cv_policy_max_extent(self.cv_policy_max_extent)
decor.discretization(policy)
cell = arbor.cable_cell(tree, labels, decor)
return cell
Vm=e_pas,
)
### Remaining parameters
for block in fit['genome']:
mech = block['mechanism'] or 'pas'
region = block['section']
name = block['name'][:-(len(mech) + 1)]
mechs[(mech, region)][name] = block['value']
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:
m = arbor.mechanism(mech, vs)
cell.paint(region, m)
print("OK")
except Exception as e:
print("ERROR")
print(" ->", e)
# Run the simulation, collecting voltages
print('Simulation', end=' ')
model = arbor.single_cell_model(cell)
model.probe('voltage', 'center', frequency=10000)
model.run(tfinal=1500)
print('DONE')
for t in model.traces:
ts = t.time[:]
volts[i] = t.value[:]
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
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 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)
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)
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)
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")
# neuroML: <channelDensity id="k_slow_all" ionChannel="k_slow" condDensity="2 mS_per_cm2" erev="-60 mV" ion="k"/>
k_slow = arbor.mechanism("k_slow")
# neuroML: <channelDensity id="k_fast_all" ionChannel="k_fast" condDensity="0.2 mS_per_cm2" erev="-60 mV" ion="k"/>
k_fast = arbor.mechanism("k_fast")
# neuroML: <species id="ca" concentrationModel="CaPool" ion="ca" initialConcentration="0 mM" initialExtConcentration="2E-6 mol_per_cm3"/>
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")
# Add locsets to the label dictionary.
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.')
if k == 'section':
continue
ion = k[1:]
print(f'| {k:<3} | {region:6} | {v:10} |')
cell.paint(region, arbor.ion(ion, rev_pot=float(v)))
log_m = []
log_p = []
# Setup mechanisms and parameters
print('Setting up mechanisms')
## Now paint the cell using the dict
for (mech, region), vs in mechs.items():
try:
if mech != 'pas':
m = arbor.mechanism(mech, vs)
for k, v in vs.items():
log_p.append(f'| {mech:10} | {region:5} | {k:8} | {float(v):>12.6g} |')
log_m.append(f'||')
cell.paint(region, m)
else:
m = arbor.mechanism('pas', {'e': vs['e'], 'g': vs['g']})
for k, v in vs.items():
if k in {'e', 'g'}:
log_p.append(f'| {mech:10} | {region:5} | {k:8} | {float(v):>12.6g} |')
cell.paint(region, m)
cell.paint(region, cm=vs["cm"]/100, rL=vs["Ra"])
except Exception as e:
print("ERROR")
print("When trying to set", mech, vs)
print(" ->", e)
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))
# !\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)
