Pyramidal neuron, fast, regular, and irregular spiking interneurons (Konstantoudaki et al 2014)

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Accession:168310
This is a model network of prefrontal cortical microcircuit based primarily on rodent data. It includes 16 pyramidal model neurons, 2 fast spiking interneuron models, 1 regular spiking interneuron model and 1 irregular spiking interneuron model. The goal of the paper was to use this model network to determine the role of specific interneuron subtypes in persistent activity
Reference:
1 . Konstantoudaki X, Papoutsi A, Chalkiadaki K, Poirazi P, Sidiropoulou K (2014) Modulatory effects of inhibition on persistent activity in a cortical microcircuit model. Front Neural Circuits 8:7 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex spiking irregular interneuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I_Ks; I_KD;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Synchronization; Active Dendrites;
Implementer(s): Sidiropoulou, Kyriaki [sidirop at imbb.forth.gr]; Konstantoudaki, Xanthippi [xeniakons at gmail.com];
Search NeuronDB for information about:  GabaA; GabaB; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I_Ks; I_KD; Gaba; Glutamate;
// This function creates a new graphical display and allows printing
// of graphs to eps files.
// edited by Yiota Poirazi, July 2001, poirazi@LNC.usc.edu

objref win[200]
ngraph = 0

proc addgraph() {       // define subroutine to add a new graph
                        // addgraph("variable", minvalue, maxvalue)
        ngraph = ngraph+1
        windex = ngraph-1
        win[windex] = new Graph()
        win[windex].size(0,tstop,$2,$3)
//      win[windex].view(0,$2,tstop,$3-$2,0,0,600,100)  // only for printing
        win[windex].xaxis()
        win[windex].yaxis()
        win[windex].label(0.1,1.0)
        win[windex].addvar($s1,1,0)
        win[windex].save_name("graphList[0].")
        graphList[0].append(win[windex])
}

proc addgraph_and_soma() {      // define subroutine to add a new graph
                                // addgraph("variable", minvalue, maxvalue)
        ngraph = ngraph+1
        windex = ngraph-1
        win[windex] = new Graph()
        win[windex].size(0,tstop,$2,$3)
//      win[windex].view(0,$2,tstop,$3-$2,0,0,600,100)  // only for printing
        win[windex].xaxis()
        win[windex].yaxis()
        win[windex].label(0.1,1.0)
        win[windex].addvar($s1,5,0)
        win[windex].addvar("soma.v(0.5)",1,0)
        win[windex].save_name("graphList[0].")
        graphList[0].append(win[windex])
}


if(ismenu==0) {
  nrnmainmenu()                 // create main menu
  nrncontrolmenu()              // crate control menu
  ismenu=1
}
proc addgraph_2() {             // define subroutine to add a new graph
                                // addgraph("variable", minvalue, maxvalue)
        ngraph = ngraph+1
        windex = ngraph-1
        win[windex] = new Graph()
        win[windex].size($2,$3,$4,$5)
//      win[windex].view(0,$2,tstop,$3-$2,0,0,600,100)  // only for printing
        win[windex].xaxis()
        win[windex].yaxis()
        win[windex].label(0.1,1.0)
        win[windex].addvar($s1,1,0)
        win[windex].save_name("graphList[0].")
        graphList[0].append(win[windex])
}


proc graph_label() {             // define subroutine to re-label a graph
                                 // graph_label("variable", minvalue, maxvalue)
        win[windex].erase_all()                        
        win[windex].size($2,$3,$4,$5)
        win[windex].xaxis()
        win[windex].yaxis()
        win[windex].label(0.1,1)
        win[windex].addvar($s1,1,0)

}

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