Allen Institute: Rorb-IRES2-Cre-D VISp layer 5 473561660

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This is an Allen Cell Types Database model of a Rorb-IRES2-Cre-D neuron from layer 5 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.
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 5 interneuron;
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:
Simulation Environment: NEURON; Python;
Model Concept(s): Parameter Fitting; Calcium dynamics; Vision;
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
Store a model's results, where the model is implemented using the Allen Brain SDK

# running an SDK model based on example at:

import os
import sys
import numpy
import json

# switch to the directory containing the script
# solution modified from
dirname = os.path.dirname(sys.argv[0])
if dirname:

os.system('nrnivmodl modfiles')

from allensdk.model.biophys_sim.config import Config
from allensdk.model.biophysical_perisomatic.utils import Utils
from allensdk.core.dat_utilities import DatUtilities

description = Config().load('manifest.json')
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'))

# configure a simple current-clamp stimulus to generate some spikes
ic = h.IClamp(0.5, sec=h.soma[0])
ic.delay = 200
ic.dur = 1000

junction_potential =['fitting'][0]['junction_potential']

currents = [270, 170, 110]
data = {'currents': currents, 'L': sum(sec.L for sec in h.allsec())}
h.tstop = 1500

for current in currents:
    ic.amp = current / 1000.
    vec = utils.record_values()
    h.dt = 0.00625
    data[current] = [[t / 1000., v - junction_potential] for t, v in zip(vec['t'], vec['v'])]

with open('../../temp_results_sdk.json', 'w') as f:

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