Allen Institute: Scnn1a-Tg3-Cre VISp layer 4 329321704

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Accession:184142
This is an Allen Cell Types Database model of a Scnn1a-Tg3-Cre neuron from layer 4 of the mouse primary visual cortex. The model was based on a traced morphology after filling the cell with biocytin and optimized using experimental electrophysiology data recorded from the same cell. The electrophysiology data was collected in a highly standardized way to facilitate comparison across all cells in the database. The model was optimized by a genetic algorithm that adjusted the densities of conductances placed at the soma to match experimentally-measured features of action potential firing. Data and models from the Allen Cell Types Database are made available to the community under the Allen Institute's Terms of Use and Citation Policy.
Reference:
1 . Allen Institute (2015) Documentation Allen Cell Types Database
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex layer 4 pyramidal cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Parameter Fitting; Calcium dynamics; Vision;
Implementer(s):
Search NeuronDB for information about:  I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca;
Files displayed below are from the implementation
from neuron import h, gui

def load_swc(filename, cell, use_axon=True, xshift=0, yshift=0, zshift=0):
    """load an SWC from filename and instantiate inside cell"""

    name_form = {1: 'soma[%d]', 2: 'axon[%d]', 3: 'dend[%d]', 4: 'apic[%d]'}

    # a helper library, included with NEURON
    h.load_file('import3d.hoc')

    # load the data. Use Import3d_SWC_read for swc, Import3d_Neurolucida3 for
    # Neurolucida V3, Import3d_MorphML for MorphML (level 1 of NeuroML), or
    # Import3d_Eutectic_read for Eutectic.
    morph = h.Import3d_SWC_read()
    morph.input(filename)

    # easiest to instantiate by passing the loaded morphology to the Import3d_GUI
    # tool; with a second argument of 0, it won't display the GUI, but it will allow
    # use of the GUI's features
    i3d = h.Import3d_GUI(morph, 0)

    # get a list of the swc section objects
    swc_secs = i3d.swc.sections
    swc_secs = [swc_secs.object(i) for i in xrange(int(swc_secs.count()))]

    # initialize the lists of sections
    cell.soma, cell.apic, cell.dend, cell.axon = [], [], [], []
    sec_list = {1: cell.soma, 2: cell.axon, 3: cell.dend, 4: cell.apic}

    # name and create the sections
    real_secs = {}
    for swc_sec in swc_secs:
        cell_part = int(swc_sec.type)

        # skip everything else if it's an axon and we're not supposed to
        # use it... or if is_subsidiary
        if (not(use_axon) and cell_part == 2) or swc_sec.is_subsidiary:
            continue
        
        # figure out the name of the new section
        if cell_part not in name_form:
            raise Exception('unsupported point type')
        name = name_form[cell_part] % len(sec_list[cell_part])

        # create the section
        sec = h.Section(cell=cell, name=name)
        
        # connect to parent, if any
        if swc_sec.parentsec is not None:
            sec.connect(real_secs[swc_sec.parentsec.hname()](swc_sec.parentx))

        # define shape
        if swc_sec.first == 1:
            h.pt3dstyle(1, swc_sec.raw.getval(0, 0), swc_sec.raw.getval(1, 0),
                        swc_sec.raw.getval(2, 0), sec=sec)

        j = swc_sec.first
        xx, yy, zz = [swc_sec.raw.getrow(i).c(j) for i in xrange(3)]
        dd = swc_sec.d.c(j)
        if swc_sec.iscontour_:
            # never happens in SWC files, but can happen in other formats supported
            # by NEURON's Import3D GUI
            raise Exception('Unsupported section style: contour')

        if dd.size() == 1:
            # single point soma; treat as sphere
            x, y, z, d = [dim.x[0] for dim in [xx, yy, zz, dd]]
            for xprime in [x - d / 2., x, x + d / 2.]:
                h.pt3dadd(xprime + xshift, y + yshift, z + zshift, d, sec=sec)
        else:
            for x, y, z, d in zip(xx, yy, zz, dd):
                h.pt3dadd(x + xshift, y + yshift, z + zshift, d, sec=sec)

        # store the section in the appropriate list in the cell and lookup table               
        sec_list[cell_part].append(sec)    
        real_secs[swc_sec.hname()] = sec

    cell.all = cell.soma + cell.apic + cell.dend + cell.axon

def main(filename='morph.swc'):
    """demo test program"""
    class Cell:
        def __str__(self):
            return 'neuron'

    cell = Cell()
    load_swc(filename, cell)
    return cell

if __name__ == '__main__':
    cell = main()

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