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(), )
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:
print('{} spikes:'.format(len(m.spikes)))
for s in m.spikes:
print(' {:7.4f}'.format(s))
else:
print('no spikes')
'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)
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
# 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)))
for s in m.spikes:
print('{:3.3f}'.format(s))
else:
print('no spikes')
