Biophysically realistic neuron models for simulation of cortical stimulation (Aberra et al. 2018)

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Accession:241165
This archive instantiates the single-cell cortical models used in (Aberra et al. 2018) and sets up extracellular stimulation with either a point-current source, to simulate intracortical microstimulation (ICMS), or a uniform E-field distribution, with a monophasic, rectangular pulse waveform in both cases.
Reference:
1 . Aberra AS, Peterchev AV, Grill WM (2018) Biophysically realistic neuron models for simulation of cortical stimulation J. Neural Eng. [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism: Neocortex; Barrel cortex;
Cell Type(s): Myelinated neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Detailed Neuronal Models;
Implementer(s): Aberra, Aman [aman.aberra at duke.edu];
/
AberraEtAl2018
cells
L4_LBC_cACint209_2
hoc_recordings
mechanisms
morphology
python_recordings
synapses
README *
.provenance.json
biophysics.hoc *
cellinfo.json
CHANGELOG *
constants.hoc *
creategui.hoc *
createsimulation.hoc
current_amps.dat
init.hoc *
LICENSE *
morphology.hoc
mosinit.hoc *
ringplot.hoc *
run.py
run_hoc.sh *
run_py.sh *
run_RmpRiTau.py
run_RmpRiTau_py.sh *
template.hoc
VERSION *
                            
#!/usr/bin/env python

"""Python script to run cell model"""


"""
/* Copyright (c) 2015 EPFL-BBP, All rights reserved.

THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJECT
BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN
IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
To view a copy of this license, visit
http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode or send a letter to
Creative Commons, 171 Second Street, Suite 300,
San Francisco, California, 94105, USA.
"""

"""
 * @file run.py
 * @brief Run simulation using pyneuron
 * @author Werner Van Geit @ BBP
 * @date 2015
"""

# pylint: disable=C0325, W0212, F0401, W0612, F0401

import os
import neuron
import numpy
import sys


def create_cell(add_synapses=True):
    """Create the cell model"""
    # Load morphology
    neuron.h.load_file("morphology.hoc")
    # Load biophysics
    neuron.h.load_file("biophysics.hoc")
    # Load main cell template
    neuron.h.load_file("template.hoc")

    # Instantiate the cell from the template

    print("Loading cell cACint209_L4_LBC_66ec8fed8f")
    cell = neuron.h.cACint209_L4_LBC_66ec8fed8f(1 if add_synapses else 0)
    return cell


def create_stimuli(cell, step_number):
    """Create the stimuli"""

    print('Attaching stimulus electrodes')

    stimuli = []
    step_amp = [0] * 3

    with open('current_amps.dat', 'r') as current_amps_file:
        first_line = current_amps_file.read().split('\n')[0].strip()
        hyp_amp, step_amp[0], step_amp[1], step_amp[2] = first_line.split(' ')

    iclamp = neuron.h.IClamp(0.5, sec=cell.soma[0])
    iclamp.delay = 700
    iclamp.dur = 2000
    iclamp.amp = float(step_amp[step_number - 1])
    print('Setting up step current clamp: '
          'amp=%f nA, delay=%f ms, duration=%f ms' %
          (iclamp.amp, iclamp.delay, iclamp.dur))

    stimuli.append(iclamp)

    hyp_iclamp = neuron.h.IClamp(0.5, sec=cell.soma[0])
    hyp_iclamp.delay = 0
    hyp_iclamp.dur = 3000
    hyp_iclamp.amp = float(hyp_amp)
    print('Setting up hypamp current clamp: '
          'amp=%f nA, delay=%f ms, duration=%f ms' %
          (hyp_iclamp.amp, hyp_iclamp.delay, hyp_iclamp.dur))

    stimuli.append(hyp_iclamp)

    return stimuli


def create_recordings(cell):
    """Create the recordings"""
    print('Attaching recording electrodes')

    recordings = {}

    recordings['time'] = neuron.h.Vector()
    recordings['soma(0.5)'] = neuron.h.Vector()

    recordings['time'].record(neuron.h._ref_t, 0.1)
    recordings['soma(0.5)'].record(cell.soma[0](0.5)._ref_v, 0.1)

    return recordings


def run_step(step_number, plot_traces=None):
    """Run step current simulation with index step_number"""

    cell = create_cell(add_synapses=False)
    stimuli = create_stimuli(cell, step_number)
    recordings = create_recordings(cell)

    # Overriding default 30s simulation,
    print('Setting simulation time to 3s for the step currents')
    neuron.h.tstop = 3000

    print('Disabling variable timestep integration')
    neuron.h.cvode_active(0)

    print('Running for %f ms' % neuron.h.tstop)
    neuron.h.run()

    time = numpy.array(recordings['time'])
    soma_voltage = numpy.array(recordings['soma(0.5)'])

    recordings_dir = 'python_recordings'

    soma_voltage_filename = os.path.join(
        recordings_dir,
        'soma_voltage_step%d.dat' % step_number)
    numpy.savetxt(
            soma_voltage_filename,
            numpy.transpose(
               numpy.vstack((
                    time,
                    soma_voltage))))

    print('Soma voltage for step %d saved to: %s'
          % (step_number, soma_voltage_filename))

    if plot_traces:
        import pylab
        pylab.figure()
        pylab.plot(recordings['time'], recordings['soma(0.5)'])
        pylab.xlabel('time (ms)')
        pylab.ylabel('Vm (mV)')
        pylab.gcf().canvas.set_window_title('Step %d' % step_number)


def init_simulation():
    """Initialise simulation environment"""

    neuron.h.load_file("stdrun.hoc")
    neuron.h.load_file("import3d.hoc")

    print('Loading constants')
    neuron.h.load_file('constants.hoc')


def main(plot_traces=True):
    """Main"""

    # Import matplotlib to plot the traces
    if plot_traces:
        import matplotlib
        matplotlib.rcParams['path.simplify'] = False

    init_simulation()

    for step_number in range(1, 4):
        run_step(step_number, plot_traces=plot_traces)

    if plot_traces:
        import pylab
        pylab.show()

if __name__ == '__main__':
    if len(sys.argv) == 1:
        main(plot_traces=True)
    elif len(sys.argv) == 2 and sys.argv[1] == '--no-plots':
        main(plot_traces=False)
    else:
        raise Exception(
            "Script only accepts one argument: --no-plots, not %s" %
            str(sys.argv))

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