Schiz.-linked gene effects on intrinsic single-neuron excitability (Maki-Marttunen et al. 2016)

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Accession:169457
Python scripts for running NEURON simulations that model a layer V pyramidal cell with certain genetic variants implemented. The genes included are obtained from genome-wide association studies of schizophrenia.
Reference:
1 . Mäki-Marttunen T, Halnes G, Devor A, Witoelar A, Bettella F, Djurovic S, Wang Y, Einevoll GT, Andreassen OA, Dale AM (2016) Functional Effects of Schizophrenia-Linked Genetic Variants on Intrinsic Single-Neuron Excitability: A Modeling Study. Biol Psychiatry Cogn Neurosci Neuroimaging 1:49-59 [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:
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I K,leak; I M; I h; I K,Ca; I A, slow; Ca pump;
Gap Junctions:
Receptor(s):
Gene(s): Nav1.1 SCN1A; Nav1.7 SCN9A; Cav3.3 CACNA1I; Cav1.3 CACNA1D; Cav1.2 CACNA1C; Kv2.1 KCNB1; HCN1;
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Coincidence Detection; Active Dendrites; Detailed Neuronal Models; Schizophrenia;
Implementer(s): Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic GLU cell; I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I K,leak; I M; I h; I K,Ca; I A, slow; Ca pump;
// Author: Etay Hay, 2011
//    Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of
//    Dendritic and Perisomatic Active Properties
//    (Hay et al., PLoS Computational Biology, 2011) 
//
// Template for models of L5 Pyramidal Cell

begintemplate L5PCtemplate
  public init
  public locateSites, getLongestBranch
  public soma, dend, apic, axon, getAbsSecIndex
  public all, somatic, apical, axonal, basal, nSecSoma, nSecApical, nSecBasal, nSecAxonal, nSecAll, nSecAxonalOrig, SecSyn, distribute_channels
  objref SecSyn, this
  objref all, somatic, apical, axonal, basal
  strdef tstr

//$s1 - morphology file name
proc init() {localobj nl,import
	all = new SectionList()
	somatic = new SectionList()
	basal = new SectionList()
	apical = new SectionList()
	axonal = new SectionList()
	forall delete_section()

  nl = new Import3d_Neurolucida3()
  nl.quiet = 0
  nl.input($s1)
  import = new Import3d_GUI(nl, 0)
  import.instantiate(this)
  geom_nseg()
  biophys()
	forsec this.all {
		if(diam == 0){
	    diam =  1
	    printf("Error : Morphology problem with section [%s] 0 diam \n", secname())
		}
  }
}

create soma[1], dend[1], apic[1], axon[1]

proc geom() {
}

proc geom_nseg() {local nSec, L1, L2, D1, D2, nSeg1, nSeg2
  soma area(.5) // make sure diam reflects 3d points
  nSec = 0
  forsec all {
    nseg = 1 + 2*int(L/40)
    nSec = nSec + 1
  }

  nSecAll = nSec
  print nSecAll
  nSec = 0
  forsec somatic { nSec = nSec + 1}
  nSecSoma	= 	nSec
  print nSecSoma
  nSec = 0
  forsec apical { nSec = nSec + 1}
  nSecApical= 	nSec
  print nSecApical
  nSec = 0
  forsec basal { nSec = nSec + 1}
  nSecBasal	= 	nSec
  print nSecBasal
  nSec = 0
  forsec axonal { nSec = nSec + 1}
  nSecAxonalOrig = nSecAxonal	= 	nSec
  print nSecAxonal
}

proc biophys() {localobj bp
	delete_axon()
	area(0.5)
	distance()
	access soma

  bp = new L5PCbiophys()
  bp.biophys(this)
}

// deleting axon, keeping only first 60 micrometers
proc delete_axon(){
    forsec axonal{delete_section()}
    create axon[2]
    access axon[0]{
      L= 30
      diam = 1
      nseg = 1+2*int(L/40)
      all.append()
      axonal.append()
    }
    access axon[1]{
      L= 30
      diam = 1
      nseg = 1+2*int(L/40)
      all.append()
      axonal.append()
    }

  nSecAxonal = 2
  connect axon(0), soma(0.5)
  connect axon[1](0), axon[0](1) 
  access soma
}

proc distribute_channels()	{local dist,val,base,maxLength
	base = $8
	soma distance()
	maxLength = getLongestBranch($s1)

	forsec $s1		{
		if(0==strcmp($s2,"Ra")){
			Ra = $8
		} else {
			for(x) {
				if ($3==3) {
					dist = distance(x)
				} else {
					dist = distance(x)/maxLength
				}
				val = calculate_distribution($3,dist,$4,$5,$6,$7,$8)
				sprint(tstr,"%s(%-5.10f) = %-5.10f",$s2,x,val)
				execute(tstr)
			}
		}
	}
}

// $1 is the distribution type:
//     0 linear, 1 sigmoid, 2 exponential
//     3 step for absolute distance (in microns)
func calculate_distribution()	{local value
	if ($1==0)	{value = $3 + $2*$4}
	if ($1==1) {value = $3 + ($4/(1+exp(($2-$5)/$6)))}
  	if ($1==2) {value = $3 + $6*exp($4*($2-$5))}
	if ($1==3) {
		if (($2 > $5) && ($2 < $6)) {
			value = $3
		} else {
			value = $4
		}
	}
	value = value*$7
	return value
}

// $s1 section
func getLongestBranch(){local maxL,d localobj distallist,sref
    sprint(tstr,"%s distance()",$s1)
    execute(tstr,this)    
    
  	if(0==strcmp($s1,"axon")){
      sprint(tstr,"%s[0] distance(1)",$s1)
      execute(tstr,this)    
  	}

		maxL = 0
		d = 0
		distallist = new SectionList()
		forsec $s1 {
			sref = new SectionRef()
			if (sref.nchild==0) distallist.append()
		}
		forsec distallist{
			d = distance(1)
			if(maxL<d) maxL = d
		}
		// for the soma case
		if (maxL == 0) {
      $s1 {
        maxL = L
      }
    }
		return maxL
	}

// $s1 section
// $2 distance x in micrometers
// return list of [1,2] vectors  - of the appropriate section and the location in each vector
obfunc locateSites() {local maxL,site,d0,d1,siteX,i localobj vv,ll
	ll = new List()

  sprint(tstr,"%s distance()",$s1)
  execute(tstr,this)    
    
	if(0==strcmp($s1,"axon")){
    sprint(tstr,"%s[0] distance(1)",$s1)
    execute(tstr,this)    
	}

	maxL = getLongestBranch($s1)
	site = $2
	i = 0
	forsec $s1 {
    if (distance(0) < distance(1)) {
  		d0 = distance(0)
  		d1 = distance(1)
  	} else {
  		d1 = distance(0)
  		d0 = distance(1)
  	}

    if (site <= d1 && site >= d0) {
      siteX = (site-d0)/(d1-d0)
      secNum = i
      vv = new Vector()
      ll.append(vv.append(secNum,siteX))
		}
		i = i+1
	}
  return ll
}

func getAbsSecIndex(){ local nAbsInd, index  localobj str,strObj
    strObj  =  new StringFunctions()
    str     =  new String()
    nAbsInd = 0
    index   = 0

    if(strObj.substr($s1, "soma") > 0) {
        strObj.tail($s1, "soma", str.s)
        if(sscanf(str.s, "%*c%d", &index) < 0) {
            index = 0
        }
        nAbsInd = index
    }else if (strObj.substr($s1, "axon") >0) {
        strObj.tail($s1, "axon", str.s)
        if(sscanf(str.s, "%*c%d", &index) < 0) {
            index = 0
        }
        nAbsInd = nSecSoma + index
    }else if (strObj.substr($s1, "dend") >0) {
        strObj.tail($s1, "dend", str.s)
        if(sscanf(str.s, "%*c%d", &index) < 0) {
            index = 0
        }
        nAbsInd = nSecSoma + nSecAxonalOrig + index
    }else if (strObj.substr($s1, "apic") > 0) {
        strObj.tail($s1, "apic", str.s)
        if(sscanf(str.s, "%*c%d", &index) < 0) {
            index = 0
        }
        nAbsInd = nSecSoma + nSecAxonalOrig + nSecBasal + index
    }
    return nAbsInd
}


endtemplate L5PCtemplate

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