SCZ-associated variant effects on L5 pyr cell NN activity and delta osc. (Maki-Marttunen et al 2018)

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Accession:237469
" … Here, using computational modeling, we show that a common biomarker of schizophrenia, namely, an increase in delta-oscillation power, may be a direct consequence of altered expression or kinetics of voltage-gated ion channels or calcium transporters. Our model of a circuit of layer V pyramidal cells highlights multiple types of schizophrenia-related variants that contribute to altered dynamics in the delta frequency band. Moreover, our model predicts that the same membrane mechanisms that increase the layer V pyramidal cell network gain and response to delta-frequency oscillations may also cause a decit in a single-cell correlate of the prepulse inhibition, which is a behavioral biomarker highly associated with schizophrenia."
Reference:
1 . Mäki-Marttunen T, Krull F, Bettella F, Hagen E, Næss S, Ness TV, Moberget T, Elvsåshagen T, Metzner C, Devor A, Edwards AG, Fyhn M, Djurovic S, Dale AM, Andreassen OA, Einevoll GT (2019) Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations. Cereb Cortex 29:875-891 [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): Ca pump; I A, slow; I h; I K; I K,Ca; I K,leak; I L high threshold; I M; I Na,p; I Na,t; I T low threshold;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; NMDA; Gaba;
Gene(s): Cav1.2 CACNA1C; Cav1.3 CACNA1D; Cav3.3 CACNA1I; HCN1; Kv2.1 KCNB1; Nav1.1 SCN1A; PMCA ATP2B2;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON; Python; LFPy;
Model Concept(s): Schizophrenia; Oscillations;
Implementer(s): Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; AMPA; NMDA; Gaba; 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; Gaba; Glutamate;
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scznet
haymod
models
morphologies
README.html
Ca_HVA.mod *
Ca_LVAst.mod *
CaDynamics_E2.mod *
epsp.mod *
Ih.mod *
Im.mod *
K_Pst.mod *
K_Tst.mod *
Nap_Et2.mod *
NaTa_t.mod *
SK_E2.mod *
SKv3_1.mod *
calcifcurves.py
calcifcurves_comb.py
collectppispthrcoeff300_relthr.py
collectscalings_cs.py
collectthresholddistalamps300.py
copydata.sh
drawppiranges.py
drawsubthppiamps_comb.py
findsubthppi300_relthr.py
findsubthppi300_relthr_comb_one.py
findthresholddistalamp300_control.py
findthresholddistalamps300.py
findthresholddistalamps300_comb.py
mutation_stuff.py *
mutation_stuff.pyc
mutindexlist.sav
mytools.py *
mytools.pyc
ppi300_relthr_comb_recordSK.py
presaved.tar.gz
runcontrol.py
savesynapselocations300.py
scalemutations_cs.py
testsubthppi300_comb_fixed.py
                            
#Copied from findppi300_relthr.py 23.11.2017
from neuron import h
import matplotlib
matplotlib.use('Agg')
import numpy
from pylab import *
import mytools
import pickle
import time
import sys
import random

random.seed(1)

v0 = -80
ca0 = 0.0001
proximalpoint = 400
distalpoint = 720
BACdt = 5.0
fs = 8
xs = range(700,1150,50);
tstop = 11000.0
currCoeff = 0.9 # use the threshold current I*1.1 for inducing the first spike, and I*1.1*2 for the second spike 
ITERS = 20#
PPIdts = range(0,500,2)
#PPIdts = range(50,500,50)
maxLens = [1300,1185]

import mutation_stuff
MT = mutation_stuff.getMT()
defVals = mutation_stuff.getdefvals()
defValsOrig = mutation_stuff.getdefvals()
keyList = defVals.keys()
for idefval in range(0,len(keyList)):
  if type(defVals[keyList[idefval]]) is not list:
    defVals[keyList[idefval]] = [defVals[keyList[idefval]], defVals[keyList[idefval]]] #make the dictionary values [somatic, apical]
    defValsOrig[keyList[idefval]] = [defValsOrig[keyList[idefval]], defValsOrig[keyList[idefval]]] #make the dictionary values [somatic, apical]
updatedVars = ['somatic','apical','basal'] # the possible classes of segments that defVals may apply to
whichDefVal = [0,1,0]                      # use the defVal[0] for somatic and basal segments and defVal[1] for apical segments
unpicklefile = open('scalings_cs.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
theseCoeffsAllAll = unpickledlist[0]
theseMutValsAllAll = unpickledlist[2]

unpicklefile = open('thresholddistalamp300_control.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
gs_control = unpickledlist[0]
Nsyns = unpickledlist[1]
maxSynsPerSeg = unpickledlist[2]

unpicklefile = open('synlocs300.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
synlocsAll = unpickledlist[3]

gCoeffsAllAll = []

def nanint(x):
  if isnan(x):
    return nan
  return int(x)
def nanintlist(x,mylist):
  if isnan(x):
    return nan
  return mylist[int(x)]

maxIDtab = array([[126, 190, 294, 314, nan, 334, nan, nan, 370, nan, nan, nan, 422, 442, nan]])
IDtab = r_[(maxIDtab-1)/4] # map itercounters to counters, i.e., 1-4 -> 0, 5-8 -> 1, ..., 457-460 -> 114

unpicklefile = open('mutindexlist.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
mutinds = unpickledlist[:]
IDtab = [[nanintlist(x,mutinds) for x in y] for y in IDtab]
mutIDs = IDtab[0]
print "mutIDs="+str(mutIDs)
time.sleep(1)


for icell in range(0,1):
  synlocs = synlocsAll[icell]
  morphology_file = "morphologies/cell"+str(icell+1)+".asc"
  biophys_file = "models/L5PCbiophys3.hoc"
  template_file = "models/L5PCtemplate.hoc"

  theseCoeffsAll = theseCoeffsAllAll[icell]

  gCoeffsAll = []

  h("""
load_file("stdlib.hoc")
load_file("stdrun.hoc")
objref cvode
cvode = new CVode()
cvode.active(1)
load_file("import3d.hoc")
objref L5PC
load_file(\""""+biophys_file+"""\")
load_file(\""""+template_file+"""\")
L5PC = new L5PCtemplate(\""""+morphology_file+"""\")
objref st1
st1 = new IClamp(0.5)
L5PC.soma st1
forsec L5PC.somatic {
}
forsec L5PC.apical {
}
L5PC.distribute_channels("apic","gIhbar_Ih",2,-0.8696,3.6161,0.0,1.0*2.0870,0.0002)
L5PC.distribute_channels("apic","gCa_HVAbar_Ca_HVA",3,1.0,0.1,685.0,885.0,1.0*0.000555)
L5PC.distribute_channels("apic","gCa_LVAstbar_Ca_LVAst",3,1.0,0.01,685.0,885.0,1.0*0.0187)
objref vsoma, vdend, recSite, vdend2, isoma, cadend, cadend2, casoma, gskdend,iskdend,ikdend
vsoma = new Vector()
casoma = new Vector()
vdend = new Vector()
cadend = new Vector()
vdend2 = new Vector()
cadend2 = new Vector()
gskdend = new Vector()
iskdend = new Vector()
ikdend = new Vector()
objref sl,st2,ns,syn1,syn2,con1,isyn, tvec, syns["""+str(2*Nsyns)+"""]
isyn = new Vector()
tvec = new Vector()
sl = new List()
double siteVec[2]
sl = L5PC.locateSites("apic","""+str(distalpoint)+""")
maxdiam = 0
for(i=0;i<sl.count();i+=1){
  dd1 = sl.o[i].x[1]
  dd = L5PC.apic[sl.o[i].x[0]].diam(dd1)
  if (dd > maxdiam) {
    j = i
    maxdiam = dd
  }
}
siteVec[0] = sl.o[j].x[0]
siteVec[1] = sl.o[j].x[1]
print "distalpoint gCa_HVA: ", L5PC.apic[siteVec[0]].gCa_HVAbar_Ca_HVA
print "distalpoint gCa_LVA: ", L5PC.apic[siteVec[0]].gCa_LVAstbar_Ca_LVAst
access L5PC.apic[siteVec[0]]
cvode.record(&v(siteVec[1]),vdend,tvec)
cvode.record(&cai(siteVec[1]),cadend,tvec)
cvode.record(&ik(siteVec[1]),ikdend,tvec)
cvode.record(&ik_SK_E2(siteVec[1]),iskdend,tvec)
cvode.record(&gSK_E2_SK_E2(siteVec[1]),gskdend,tvec)
st2 = new IClamp(siteVec[1])
st2.amp = 0
L5PC.apic[siteVec[0]] {
  st2
  syn1 = new epsp(siteVec[1])
  syn1.tau0 = 0.5
  syn1.tau1 = 5
  syn1.onset = 145 + """+str(BACdt)+""" 
  syn1.imax = 0
  syn2 = new epsp(siteVec[1])
  syn2.tau0 = 0.5
  syn2.tau1 = 5
  syn2.onset = 145 + """+str(BACdt)+""" 
  syn2.imax = 0
  cvode.record(&syn1.i,isyn,tvec)
}
access L5PC.soma
cvode.record(&v(0.5),vsoma,tvec)
cvode.record(&cai(0.5),casoma,tvec)
""")
  for istim in range(0,Nsyns):
    h("""
siteVec[0] = """+str(synlocs[istim][0])+"""
siteVec[1] = """+str(synlocs[istim][1])+"""
access L5PC.apic[siteVec[0]]
L5PC.apic[siteVec[0]] {
  syns["""+str(istim)+"""] = new AlphaSynapse(siteVec[1])
  syns["""+str(istim)+"""].e = 0
  syns["""+str(istim)+"""].tau = 5
  syns["""+str(istim)+"""].onset = 10000 + """+str(BACdt)+"""
  syns["""+str(istim+Nsyns)+"""] = new AlphaSynapse(siteVec[1])
  syns["""+str(istim+Nsyns)+"""].e = 0
  syns["""+str(istim+Nsyns)+"""].tau = 5
  syns["""+str(istim+Nsyns)+"""].onset = 10000 + """+str(BACdt)+"""
}
""")
  #extra"""

  styles = ['g-','g-','g-','g-','g-','g-','g-','g-','g-']
  #cols = ['#aaffaa','#aaffaa','#66ff66','#66aaaa','#00aaaa','#00aaaa']
  #cols = ['#00aaaa','#00bb77','#11cc44','#11dd11','#55ee00','#99dd00']
  #cols = ['#00aaaa','#11cc44','#55ee00','#bbaa00','#ee6600','#ff0000', '#aa00aa','#772277','#333333']
  cols = ['#444444','#012345','#aa00aa','#bbaa00','#ee6600','#ff0000', '#009999','#772277','#00cc00']
  col_control = '#2222ff'
  #yplus = [1, 2, 3, 4, 5, 6, -1, -2, -3]
  #yplus = [x+3 for x in yplus]
  yplus = [0, 0, 0, 0, 0, 0, 0, 0, 0]
  coeffCoeffs = [[0.25,0],[0.125,0],[0.5,0],[0.5,1.0/3],[0.5,2.0/3],[0.5,1.0],[-0.25,0],[-0.125,0],[-0.5,0]]

  close("all")
  f, axarr = plt.subplots(1, 1)
  iters = [0, 2, 5, 6, 8, -1]

  unpicklefile = open('thresholddistalamp300_cs'+str(icell)+'_comb.sav', 'r')
  unpickledlist = pickle.load(unpicklefile)
  unpicklefile.close()
  gsThisComb = unpickledlist[1]
  gCoeffsThisComb = []
  for iiter in range(0,len(iters)):
    if len(sys.argv) > 1 and iiter != int(sys.argv[1]):
      continue
    iter = iters[iiter]
    if iter == 5:
      continue
    defVals = mutation_stuff.getdefvals()
    keyList = defVals.keys()
    for idefval in range(0,len(keyList)):
      if type(defVals[keyList[idefval]]) is not list:
        defVals[keyList[idefval]] = [defVals[keyList[idefval]], defVals[keyList[idefval]]] #make the dictionary values [somatic, apical]
    mutText = ""
    gCoeffsThisIter = []
    gsThisIter = gsThisComb[iiter]
    for imutID in range(0,len(mutIDs)):
       if type(mutIDs[imutID]) is not list:
         continue
       igene = mutIDs[imutID][0]
       imut = mutIDs[imutID][1]
       iallmutval = mutIDs[imutID][2]

       nVals = len(MT[igene][imut])*[0]
       thesemutvars = []
       theseCoeffs = theseCoeffsAll[igene][imut]
       for imutvar in range(0,len(MT[igene][imut])):
         thesemutvars.append(MT[igene][imut][imutvar][0])
         if type(MT[igene][imut][imutvar][1]) is int or type(MT[igene][imut][imutvar][1]) is float:
           MT[igene][imut][imutvar][1] = [MT[igene][imut][imutvar][1]]
         nVals[imutvar] = len(MT[igene][imut][imutvar][1])
       cumprodnVals = cumprod(nVals)
       allmutvars = cumprodnVals[len(MT[igene][imut])-1]*[thesemutvars]
       allmutvals = []
       for iallmutvaltmp in range(0,cumprodnVals[len(MT[igene][imut])-1]):
         allmutvals.append([0]*len(thesemutvars))
       for iallmutvaltmp in range(0,cumprodnVals[len(MT[igene][imut])-1]):
         for imutvar in range(0,len(MT[igene][imut])):
           if imutvar==0:
             allmutvals[iallmutvaltmp][imutvar] = MT[igene][imut][imutvar][1][iallmutvaltmp%nVals[imutvar]]
           else:
             allmutvals[iallmutvaltmp][imutvar] = MT[igene][imut][imutvar][1][(iallmutvaltmp/cumprodnVals[imutvar-1])%nVals[imutvar]]
    
       if iter >= 0:
         thisCoeff = coeffCoeffs[iter][0]*theseCoeffs[iallmutval] + coeffCoeffs[iter][1]*(1.0 - 0.5*theseCoeffs[iallmutval])
       else:
         thisCoeff = 0
       for imutvar in range(0,len(MT[igene][imut])):
         if imutvar > 0 and imutvar%2==0:
           mutText = mutText+"\n"
         mutvars = allmutvars[iallmutval][imutvar]
         mutvals = allmutvals[iallmutval][imutvar]
         if type(mutvars) is str:
           mutvars = [mutvars]
         mutText = mutText + str(mutvars) + ": "
         for kmutvar in range(0,len(mutvars)):
           mutvar = mutvars[kmutvar]
           if mutvar.find('offm') > -1 or mutvar.find('offh') > -1 or mutvar.find('ehcn') > -1:
             newVal =  [x+mutvals*thisCoeff for x in defVals[mutvar]]
             if mutvals >= 0 and kmutvar==0:
               mutText = mutText + "+" + str(mutvals) +" mV"
             elif kmutvar==0:
               mutText = mutText  + str(mutvals) +" mV"
           else:
             newVal = [x*(mutvals**thisCoeff) for x in defVals[mutvar]]
             if kmutvar==0:
               mutText = mutText + "*" + str(mutvals)
           defVals[mutvar] = newVal[:]

           if kmutvar < len(mutvars)-1:
             mutText = mutText + ", "
           if mutvar.find('_Ih') > -1:
             updateThese = [1,1,1]
           elif mutvar.find('_Ca_HVA') > -1 or mutvar.find('_Ca_LVAst') > -1 or mutvar.find('_SKv3.1') > -1 or mutvar.find('_Ca_HVA') > -1 or mutvar.find('_SK_E2') > -1 or mutvar.find('_NaTa_t') > -1 or mutvar.find('_CaDynamics_E2') > -1:
             updateThese = [1,1,0]
           elif mutvar.find('_K_Pst') > -1 or mutvar.find('_K_Tst') > -1 or mutvar.find('_Nap_Et2') > -1:
             updateThese = [1,0,0]
           elif mutvar.find('_Im') > -1:
             updateThese = [0,1,0]
           else:
             print "Error: str=" + str(mutvar)
             updatedThese = [0,0,0]
           for iupdated in range(0,3):
             if updateThese[iupdated]:
               print """forsec L5PC."""+str(updatedVars[iupdated])+""" {
"""+mutvar+""" = """+str(newVal[whichDefVal[iupdated]])+"""
}"""
               h("""forsec L5PC."""+str(updatedVars[iupdated])+""" {
"""+mutvar+""" = """+str(newVal[whichDefVal[iupdated]])+"""
}""")
    print mutText
    thisCa = h.L5PC.soma[0].minCai_CaDynamics_E2

    for istim in range(0,Nsyns):
      h("syns["+str(istim)+"].gmax = "+str(gsThisIter*currCoeff))
      h("syns["+str(istim+Nsyns)+"].gmax = 0")
      h("syns["+str(istim+Nsyns)+"].onset = 20000")
    h("""
tstop = """+str(tstop)+"""
cai0_ca_ion = """+str(thisCa)+"""
v_init = """+str(v0)+"""
st1.amp = 0
st1.del = 200
st1.dur = 10
""")
    h.init()
    try:
      h.run()
    except RuntimeError:
      print "Too large I!"
    times=np.array(h.tvec)
    Casoma=np.array(h.casoma)
    Cadend=np.array(h.cadend)
    Vsoma=np.array(h.vsoma)
    Vdend=np.array(h.vdend)
    gSKdend=np.array(h.gskdend)
    iSKdend=np.array(h.iskdend)
    ikdend=np.array(h.ikdend)
    nSpikes_total = len(mytools.spike_times(times,Vsoma,-35,-37.5))
    
    picklelist = [theseCoeffsAllAll,times,Vsoma,Vdend,gSKdend,iSKdend,ikdend,PPIdts,MT]
    file = open('ppi_currtimecourse_cs'+str(icell)+'_comb_iiter'+str(iiter)+'.sav', 'w')
    pickle.dump(picklelist,file)
    file.close()

    mycol = col_control
    if iter >= 0:
      mycol = cols[iter]
    axarr.plot(times,1000*gSKdend,color=mycol,linewidth=2)
    axarr.set_xlim([10000,10500])
    axarr.set_xticks([10000,10100,10200,10300,10400,10500])
    axarr.set_xticklabels(['0','100','200','300','400','500'])

    axarr.set_xlabel('$t$ (ms)',fontsize=15)
    axarr.set_ylabel('$g_{SK}$ (mS/cm$^2$)',fontsize=15)
    for tick in axarr.xaxis.get_major_ticks()+axarr.yaxis.get_major_ticks():
      tick.label.set_fontsize(15)

    f.savefig('ppi_currtimecourse_cs'+str(icell)+'_comb.eps')

    for idefval in range(0,len(defVals.keys())):
         thisdefval = defVals.keys()[idefval]
         if thisdefval.find('_Im') > -1:
           h('print "L5PC.apic[0].'+thisdefval+' = ", L5PC.apic[0].'+thisdefval+', "Default = ", '+str(defVals[thisdefval][1]))

         else:
           h('print "L5PC.soma[0].'+thisdefval+' = ", L5PC.soma[0].'+thisdefval+', "Default = ", '+str(defVals[thisdefval][0]))

    #Restore default values:
    for imutID in range(0,len(mutIDs)):
      if type(mutIDs[imutID]) is not list:
        continue
      igene = mutIDs[imutID][0]
      imut = mutIDs[imutID][1]
      iallmutval = mutIDs[imutID][2]

      nVals = len(MT[igene][imut])*[0]
      thesemutvars = []
      theseCoeffs = theseCoeffsAll[igene][imut]
      for imutvar in range(0,len(MT[igene][imut])):
        thesemutvars.append(MT[igene][imut][imutvar][0])
        if type(MT[igene][imut][imutvar][1]) is int or type(MT[igene][imut][imutvar][1]) is float:
          MT[igene][imut][imutvar][1] = [MT[igene][imut][imutvar][1]]
        nVals[imutvar] = len(MT[igene][imut][imutvar][1])
      cumprodnVals = cumprod(nVals)
      allmutvars = cumprodnVals[len(MT[igene][imut])-1]*[thesemutvars]
      for imutvar in range(0,len(MT[igene][imut])):
        mutvars = allmutvars[iallmutval][imutvar]
        if type(mutvars) is str:
          mutvars = [mutvars]
        for kmutvar in range(0,len(mutvars)):
          mutvar = mutvars[kmutvar]
          newVal = defVals[mutvar]
          if mutvar.find('_Ih') > -1:
            updateThese = [1,1,1]
          elif mutvar.find('_Ca_HVA') > -1 or mutvar.find('_Ca_LVAst') > -1 or mutvar.find('_SKv3.1') > -1 or mutvar.find('_Ca_HVA') > -1 or mutvar.find('_SK_E2') > -1 or mutvar.find('_NaTa_t') > -1 or mutvar.find('_CaDynamics_E2') > -1: 
            updateThese = [1,1,0]
          elif mutvar.find('_K_Pst') > -1 or mutvar.find('_K_Tst') > -1 or mutvar.find('_Nap_Et2') > -1:
            updateThese = [1,0,0]
          elif mutvar.find('_Im') > -1:
            updateThese = [0,1,0]
          else:
            print "Error: str=" + str(mutvar)
            updatedThese = [0,0,0]
          for iupdated in range(0,3):
            if updateThese[iupdated]:
              print """forsec L5PC."""+str(updatedVars[iupdated])+""" {
"""+mutvar+""" = """+str(newVal[whichDefVal[iupdated]])+"""
}"""
              h("""forsec L5PC."""+str(updatedVars[iupdated])+""" {
"""+mutvar+""" = """+str(newVal[whichDefVal[iupdated]])+"""
}""")

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