Impact of dendritic size and topology on pyramidal cell burst firing (van Elburg and van Ooyen 2010)

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Accession:114359
The code provided here was written to systematically investigate which of the physical parameters controlled by dendritic morphology underlies the differences in spiking behaviour observed in different realizations of the 'ping-pong'-model. Structurally varying dendritic topology and length in a simplified model allows us to separate out the physical parameters derived from morphology underlying burst firing. To perform the parameter scans we created a new NEURON tool the MultipleRunControl which can be used to easily set up a parameter scan and write the simulation results to file. Using this code we found that not input conductance but the arrival time of the return current, as measured provisionally by the average electrotonic path length, determines whether the pyramidal cell (with ping-pong model dynamics) will burst or fire single spikes.
Reference:
1 . van Elburg RA, van Ooyen A (2010) Impact of dendritic size and dendritic topology on burst firing in pyramidal cells. PLoS Comput Biol 6:e1000781 [PubMed]
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 L5/6 pyramidal GLU cell;
Channel(s): I Na,t; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Activity Patterns; Bursting; Spatio-temporal Activity Patterns; Simplified Models; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Methods;
Implementer(s): van Elburg, Ronald A.J. [R.van.Elburg at ai.rug.nl];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; I Na,t; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
// Author: Ronald van Elburg  (RonaldAJ at vanElburg eu)
//	
// Affiliation:
//           Department of Artificial Intelligence
//           Groningen University
//
// NEURON script for the paper:
//
//   Ronald A.J. van Elburg and Arjen van Ooyen (2010) `Impact of dendritic size and
//   dendritic topology on burst firing in pyramidal cells', 
//   PLoS Comput Biol 6(5): e1000781. doi:10.1371/journal.pcbi.1000781.
//
// Please consult readme.txt or instructions on the usage of this file.
//
// This software is released under the GNU GPL version 3: 
// http://www.gnu.org/copyleft/gpl.html

objectvar save_window_, rvp_
objectvar scene_vector_[3]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}

//Load MultipleRunControlGUI[0] code
{
    load_file("../hoc/mrc/MultipleRunControl.hoc","MultipleRunControlGUI")
}


// Begin of manually added code (the rest is a session file)
    interactive=0
    unmod_area=0  
    load_file("../modelCellReConstruction.hoc")
    screen_update_invl=1
    
    /* AdjustModel() */
    ra=80
    remove_basal    =   0
    passive_basal   =   1
    passive_apical  =   0
    passive_soma    =   0
    remove_axon     =   0
    modBasalChannelDensity=0
    remCaDepChannelsFromSoma=0
    pruneDend11=0
    bPrintTree=0
    
    ST_AMP=0.2
    ST_DEL=400     
    tstop = 10000
    ST_DUR=tstop
    aspiny = 1
    
    // Dendritic Stimulation
    synaptic_density=0.05
    mean_interval=1000              // milliseconds   
    globSynapseStrength=0.0024      // Bernander 1994
    total_area=0
    L_total=0
    objref KSyn, KSynList
    
    bDendriticStimulation=1   
    proc createSynapses(){
        objref KSyn, KSynList
        KSynList=new List()   
        
        total_area=0
        //unmod_area=67698.57
        
        forsec "dend"{	
            for (x,0) {                
                total_area+=area(x)
            }
        }
        
        compensation_factor=unmod_area/total_area
        print "L_factor: ",L_factor, " total_area: ",total_area, " compensation_factor: ", compensation_factor
        forsec "dend"{
            for (x,0) {                
                KSyn= new SynAlphaPoisson(x)
                //total_area+=area(x)       
                KSyn.mean=mean_interval/(area(x)*synaptic_density*compensation_factor)
                KSyn.tau=0.5
                KSyn.offset=tstop-0.1
                KSyn.stim=globSynapseStrength
                KSynList.append(KSyn)
            }
        }
    }

    // Tree Topologies
    bMoveBranches=0
    
    proc customModifications(){
        
        if(bDendriticStimulation==1){
            createSynapses()
            st.amp=0
            st.dur=0
        }else{
            st.amp=ST_AMP
            st.del=ST_DEL   
            st.dur=ST_DUR
        }
    }

    fig1d()
    unmod_area=0    
    // Calculate unmodified dendritic area
    forsec "dend"{	
        for (x,0) {                
            unmod_area+=area(x)
        }
    }


    objref ImpedanceTool
    func getic(){local ic
        
        soma {
            ImpedanceTool=new Impedance()
            ImpedanceTool.loc(0.5)
            ImpedanceTool.compute(0)
            ic=1/ImpedanceTool.input(0.5) // Units: 1/[MOhm]?
        }
    
        objref ImpedanceTool
        return ic
    }
// End of  manually added code

//Begin MultipleRunControlGUI[0]
{
ocbox_ = new MultipleRunControlGUI(1)
}
{object_push(ocbox_)}
{
file_name="ScalingReconstructed/Results/Sim"
file_index_start=1
}

{tobj=new MRC_Protocol()}
	{object_push(tobj)}
	{
		output_matlab_mfile=0
		output_neuronbinary=1
		output_axontextfile=0
	}
	{object_pop()}

{protocol=tobj}

{tobj=new MRC_LoopParameter()}
	{object_push(tobj)}
	{
		name="bDendriticStimulation"
		lower_limit=0
		upper_limit=0
		stepsize=1
		use=1
		setdisplaytext()
	}
	{object_pop()}
{looppars.append(tobj)}

{tobj=new MRC_LoopParameter()}
	{object_push(tobj)}
	{
		name="L_factor"
		lower_limit=0.5
		upper_limit=2.5
		stepsize=0.1
		use=1
		setdisplaytext()
	}
	{object_pop()}
{looppars.append(tobj)}





{tobj1=types_outpar.gettypefromindex(2)}
{tobj=new MRC_OutputVariable("j4a_spikes",tobj1,protocol)}
	{object_push(tobj)}
	{
		use=1
		setdisplaytext()
	}
	{object_pop()}
{tobj1=tobj.gethandler()}
	{object_push(tobj1)}
	{
		record_start=0
		record_stop=9000
		threshold=0
		listname="soma"
		sectionname=""
		membername="v(0.5)"
		listtype=2
		useindexing=0
		isart=0
		shortname="j4a_spikes"
	}
	{object_pop()}

{outpars.append(tobj)}
{tobj1=types_outpar.gettypefromindex(1)}
{tobj=new MRC_OutputVariable("j4a_vtrace_soma",tobj1,protocol)}
	{object_push(tobj)}
	{
		use=1
		setdisplaytext()
	}
	{object_pop()}
{tobj1=tobj.gethandler()}
	{object_push(tobj1)}
	{
		record_start=0
		record_stop=9000
		sectionname="soma"
		membername="v(0.5)"
		useindexing=0
		isart=0
		shortname="j4a_vtrace_soma"
	}
	{object_pop()}

{outpars.append(tobj)}
{tobj1=types_outpar.gettypefromindex(1)}
{tobj=new MRC_OutputVariable("j4a_vtrace_dend",tobj1,protocol)}
	{object_push(tobj)}
	{
		use=0
		setdisplaytext()
	}
	{object_pop()}
{tobj1=tobj.gethandler()}
	{object_push(tobj1)}
	{
		record_start=0
		record_stop=9000
		sectionname="dend11[82]"
		membername="v(0.5)"
		useindexing=0
		isart=0
		shortname="j4a_vtrace_dend"
	}
	{object_pop()}

{outpars.append(tobj)}

{object_pop()}
{
ocbox_.map("MultipleRunControlGUI[0]", 840, 132, 392.4, 342)
}
objref ocbox_
//End MultipleRunControlGUI[0]

objectvar scene_vector_[1]
{doNotify()}

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