def run(description):
"""Main function for running a perisomatic biophysical experiment.
Parameters
----------
description : Config
All information needed to run the experiment.
"""
# configure NEURON
utils = Utils(description)
h = utils.h
# configure model
manifest = description.manifest
morphology_path = description.manifest.get_path("MORPHOLOGY")
utils.generate_morphology(morphology_path.encode("ascii", "ignore"))
utils.load_cell_parameters()
# configure stimulus and recording
stimulus_path = description.manifest.get_path("stimulus_path")
run_params = description.data["runs"][0]
sweeps = run_params["sweeps"]
junction_potential = description.data["fitting"][0]["junction_potential"]
mV = 1.0e-3
stimulus_format = manifest.get_format("stimulus_path")
output_format = manifest.get_format("output")
if stimulus_format == "NWB" and output_format == "NWB":
prepare_nwb_output(manifest.get_path("stimulus_path"), manifest.get_path("output"))
# run sweeps
for sweep in sweeps:
if stimulus_format == "NWB":
utils.setup_iclamp(stimulus_path, sweep=sweep)
elif stimulus_format == "dat":
utils.setup_iclamp_dat(stimulus_path)
vec = utils.record_values()
h.finitialize()
h.run()
# write to an NWB File
output_data = (numpy.array(vec["v"]) - junction_potential) * mV
output_times = numpy.array(vec["t"])
if output_format == "NWB":
output_path = manifest.get_path("output")
save_nwb(output_path, output_data, sweep)
elif output_format == "dat":
output_path = manifest.get_path("output", sweep)
DatUtilities.save_voltage(output_path, output_data, output_times)
def test_biophysical():
neuronal_model_id = 472451419 # get this from the web site
model_directory = "."
bp = BiophysicalApi("http://api.brain-map.org")
bp.cache_stimulus = False # don't want to download the large stimulus NWB file
bp.cache_data(neuronal_model_id, working_directory=model_directory)
os.system("nrnivmodl modfiles")
description = Config().load("manifest.json")
utils = Utils(description)
h = utils.h
manifest = description.manifest
morphology_path = manifest.get_path("MORPHOLOGY")
utils.generate_morphology(morphology_path.encode("ascii", "ignore"))
utils.load_cell_parameters()
stim = h.IClamp(h.soma[0](0.5))
stim.amp = 0.18
stim.delay = 1000.0
stim.dur = 1000.0
h.tstop = 3000.0
vec = utils.record_values()
h.finitialize()
h.run()
output_path = "output_voltage.dat"
junction_potential = description.data["fitting"][0]["junction_potential"]
mV = 1.0e-3
ms = 1.0e-3
output_data = (numpy.array(vec["v"]) - junction_potential) * mV
output_times = numpy.array(vec["t"]) * ms
DatUtilities.save_voltage(output_path, output_data, output_times)
assert numpy.count_nonzero(output_data) > 0
def test_biophysical():
neuronal_model_id = 472451419 # get this from the web site
model_directory = '.'
bp = BiophysicalApi('http://api.brain-map.org')
bp.cache_stimulus = False # don't want to download the large stimulus NWB file
bp.cache_data(neuronal_model_id, working_directory=model_directory)
os.system('nrnivmodl modfiles')
description = Config().load('manifest.json')
utils = Utils(description)
h = utils.h
manifest = description.manifest
morphology_path = manifest.get_path('MORPHOLOGY')
utils.generate_morphology(morphology_path.encode('ascii', 'ignore'))
utils.load_cell_parameters()
stim = h.IClamp(h.soma[0](0.5))
stim.amp = 0.18
stim.delay = 1000.0
stim.dur = 1000.0
h.tstop = 3000.0
vec = utils.record_values()
h.finitialize()
h.run()
output_path = 'output_voltage.dat'
junction_potential = description.data['fitting'][0]['junction_potential']
mV = 1.0e-3
ms = 1.0e-3
output_data = (numpy.array(vec['v']) - junction_potential) * mV
output_times = numpy.array(vec['t']) * ms
DatUtilities.save_voltage(output_path, output_data, output_times)
assert numpy.count_nonzero(output_data) > 0
def test_biophysical_peri():
"""
Test for backward compatibility of the perisomatic models
"""
subprocess.check_call(['nrnivmodl', 'modfiles/'])
description = Config().load('manifest.json')
utils = Utils(description)
h = utils.h
manifest = description.manifest
morphology_path = manifest.get_path('MORPHOLOGY')
utils.generate_morphology(
morphology_path.encode('ascii', 'ignore').decode("utf-8"))
utils.load_cell_parameters()
stim = h.IClamp(h.soma[0](0.5))
stim.amp = 0.35 # Sweep 47
stim.delay = 1000.0
stim.dur = 1000.0
h.tstop = 3000.0
vec = utils.record_values()
h.finitialize()
h.run()
junction_potential = description.data['fitting'][0]['junction_potential']
ms = 1.0e-3
output_data = (numpy.array(vec['v']) - junction_potential) # in mV
output_times = numpy.array(vec['t']) * ms # in s
output_path = 'output_voltage.dat'
DatUtilities.save_voltage(output_path, output_data, output_times)
num_spikes = len(
ephys_features.detect_putative_spikes(output_data, output_times))
assert num_spikes == 27 # taken from the web app
