Globus pallidus neuron models with differing dendritic Na channel expression (Edgerton et al., 2010)

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Accession:136315
A set of 9 multi-compartmental rat GP neuron models (585 compartments) differing only in their expression of dendritic fast sodium channels were compared in their synaptic integration properties. Dendritic fast sodium channels were found to increase the importance of distal synapses (both excitatory AND inhibitory), increase spike timing variability with in vivo-like synaptic input, and make the model neurons highly sensitive to clustered synchronous excitation.
References:
1 . Edgerton JR, Hanson JE, Gunay C, Jaeger D (2010) Dendritic sodium channels regulate network integration in globus pallidus neurons: a modeling study. J Neurosci 30:15146-59 [PubMed]
2 . Edgerton JR, Jaeger D (2011) Dendritic Sodium Channels Promote Active Decorrelation and Reduce Phase Locking to Parkinsonian Input Oscillations in Model Globus Pallidus Neurons J. Neurosci. 31:10919-10936
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon; Synapse; Channel/Receptor; Dendrite;
Brain Region(s)/Organism: Basal ganglia;
Cell Type(s): Globus pallidus neuron;
Channel(s): I Na,p; I Na,t; I A; I K; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Gene(s): Kv4.1 KCND1;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: GENESIS;
Model Concept(s): Action Potential Initiation; Dendritic Action Potentials; Coincidence Detection; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Synaptic Integration;
Implementer(s): Gunay, Cengiz [cgunay at emory.edu]; Edgerton, Jeremy R. [jedgert at emory.edu]; Hanson, Jesse E.; Jaeger, Dieter [djaeger at emory.edu];
Search NeuronDB for information about:  GabaA; AMPA; I Na,p; I Na,t; I A; I K; I h; I K,Ca; I Calcium; Gaba; Glutamate;
  
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Edgerton_etal_2010_GPmodel
common
matlab_reader
run_example
shellscripts
README
                            
Instructions for running simulations with the set of GP neuron models from
Edgerton JR, Hanson JE, Gunay C, Jaeger D (2010). Dendritic sodium channels 
regulate network integration in globus pallidus neurons: a modeling study. 
J Neurosci 30: 15146-59.

DIRECTORY STRUCTURE:

  common: contains the model description files and some utility functions for
    setting up a simulation.

    common/biophysics: ion channel, synapse and passive biophysics descriptions
    common/morphol: cell morphology descriptions
    common/library: scripts to create a library of template objects during the
        simulation
    common/functions: various implementation scripts for the simulations
    common/comptlists: lists of model compartments for various purposes such
        as where to put synapses, which compartments to save outputs from, etc.

  shellscripts: linux shell scripts to help run the simulations

  run_example: scripts to run two different types of example simulations

    run_example/run_slice.g: example simulations with no synaptic inputs but
        with somatic current injections like those often used in slice
        experiments.

    run_example/run_vivo.g: example simulations with synaptic inputs active
        throughout the dendritic tree. Synapses have random timing in these
        simulations.

  matlab_reader: a plugin written in C that enables you to load the
        output data into Matlab.
        --> compile using the Matlab mex compiler in a Linux shell:
          > mex -output readgenesis readgenesis.c
     

TUTORIAL:

  First, you must have genesis 2.3 installed on your machine.

  Download and unzip the model files. 

  Navigate to the run_example directory.

  To run the "slice" simulations, execute the following commands:

    > ../shellscripts/create_perlhash_param_db pars_slice.par

    > ../shellscripts/runbatch_local_perlhash.sh run_slice_example.g pars_slice.par 1 1

        This command runs a simulation using the first row of parameters listed
            in the pars_slice.par file. If it runs without any problem you
            should see a data file appear in the data_slice directory named
            1_mtype_1_scaleMeth_0_sclTau_-200_pAinjected_slice_example_run_v.bin

    > ../shellscripts/runbatch_local_perlhash.sh run_slice_example.g pars_slice.par 2 72

        This command runs each of the remaining 71 parameter combinations in the
            pars_slice.par file sequentially. Once complete, there should be
            72 data files in the data_slice directory, one for each parameter
            set.


  To run the "vivo" simulations, simply repeat the same steps with the vivo
        example scripts.

    > ../shellscripts/create_perlhash_param_db pars_vivo.par

    > ../shellscripts/runbatch_local_perlhash.sh run_vivo_example.g pars_vivo.par 1 1

    > ../shellscripts/runbatch_local_perlhash.sh run_vivo_example.g pars_vivo.par 2 18


  To visualize the data in Matlab: 
    First compile the reader:
      > mex -output readgenesis readgenesis.c
        
    Add the reader directory to your Matlab path, then run the following
        commands from within Matlab:

    % Load the data into the workspace
    >> tdat = readgenesis('data_slice/1_mtype_1_scaleMeth_0_sclTau_-200_pAinjected_slice_example_run_v.bin', 1);

    % Change the y-scale from volts to millivolts
    >> tdat = tdat .* 1e3;

    % Plot the data
    >> figure; plot([1e-4:1e-4:5], tdat);


Submitted by: 
    Jeremy R. Edgerton < jeremy.edgerton AT gmail.com >, 12/2010

Co-authors:
    Jesse E. Hanson < hanson.jesse AT gene.com >
    Cengiz Gunay < cgunay AT emory.edu >
    Dieter Jaeger < djaeger AT emory.edu >

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