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')