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
                            
#cp ../haymod3c/drawppiranges.py drawppiranges.py
from neuron import h
import matplotlib
matplotlib.use('Agg')
import numpy
from pylab import *
import mytools
import pickle
import time
import sys
#import matplotlib.pyplot
#import matplotlib.lines


morphology_file = "morphologies/cell1.asc"
biophys_file = "models/L5PCbiophys3.hoc"
template_file = "models/L5PCtemplate.hoc"
v0 = -80
ca0 = 0.0001
proximalpoint = 400
distalpoint = 620
#distalpoint = 960
BACdt = 5.0
fs = 8
DI = 70 #distance between images

import mutation_stuff
MT = mutation_stuff.getMT()
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]
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]
theseMutValsAll = unpickledlist[2]

spTimesAll = []
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 = ['#666666','#012345','#aa00aa','#bbaa00','#ee6600','#ff0000', '#00aaaa','#772277','#00cc00']
cols = ['#444444','#012345','#aa00aa','#bbaa00','#ee6600','#ff0000', '#009999','#772277','#00cc00']
yplus = [1, 2, 3, 4, 5, 6, -1, -2, -3]
yplus = [x+3 for x in yplus]
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]]

params = {'text.latex.preamble': [r"\usepackage{upgreek}"],
          'text.usetex': True}
plt.rcParams.update(params)

genelabels = ['CACNA1C (Kudrnac et al. 2009)','CACNA1C (Kudrnac et al. 2009)','CACNB2 (Cordeiro et al. 2009)','CACNB2 (Massa et al. 1995)','CACNB2 (Link et al. 2009)',
          'CACNA1D (Tan et al. 2011; \n Bock et al. 2011)','CACNA1D (Tan et al. 2011; \n Bock et al. 2011)','CACNA1D (Zhang et al. 2011; \n Perez-Alvarez et al. 2011)',
          'CACNA1I (Murbartian et al. 2004)','CACNA1S (Pirone et al. 2010)','CACNA1S (Tuluc et al. 2009)','ATP2A2 (Ji et al. 2000)','ATP2B2 (Fakira et al. 2012)',
          'ATP2B2 (Empson et al. 2010)','ATP2B2 (Ficarella et al. 2007)','SCN1A (Cestele et al. 2008)','SCN1A (Vanmolkot et al. 2007)','SCN9A (Estacion et al. 2011)',
          'SCN9A (Estacion et al. 2008)','SCN9A (Han et al. 2006)','SCN9A (Dib-Hajj et al. 2005)','KCNS3 (Shepard and Rae 1999)','KCNB1 (Bocksteins et al. 2011)',
          'KCNB1 (Bocksteins et al. 2011)','KCNB1 (Bocksteins et al. 2011)','KCNB1 (Bocksteins et al. 2011)','KCNB1 (Bocksteins et al. 2011)',
          'KCNB1 (Bocksteins et al. 2011)','KCNN3 (Wittekindt et al. 2004)','HCN1 (Ishii et al. 2007)','','','','','','','','','','','','','','','','','','','','','','','','']
labelxplus = [0,0,0,0,0,-0.6,-0.6,-0.6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
labelyplus = [0,0,0,1,0,-6,-6,-6,-3,1,0,0,0,1,0,3,0,1,1,1,0,1,0,0,0,0,0,0,-3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]


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

unpicklefile = open('ppiextraspthrcoeff300_relthr_cs.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
theseCoeffsAllAll = unpickledlist[0]
gsAllAll = unpickledlist[1]
PPIdts = unpickledlist[2]
DataAllAll = unpickledlist[3]



for icell in range(0,1):
  theseCoeffsAll = theseCoeffsAllAll[icell]
  close("all")
  f, axarr = plt.subplots(1, 1)
  counter = -1
  labelcounter = -1

  thisy = [x*1.1 for x in DataAllAll[icell][0][0][0][5]]
  firstabovethree = -1
  lastabovethree = -1
  for iy in range(0,len(thisy)):
    if thisy[iy] > 3 and firstabovethree == -1:
      firstabovethree = iy
    if thisy[iy] > 3:
      lastabovethree = iy
  xplusthis1 = 2.0*(3.0-thisy[firstabovethree-1])/(thisy[firstabovethree]-thisy[firstabovethree-1])
  xplusthis2 = 2.0*(3.0-thisy[lastabovethree])/(thisy[lastabovethree+1]-thisy[lastabovethree])
  range_control = [PPIdts[firstabovethree-1]+xplusthis1,PPIdts[lastabovethree]+xplusthis2]
  
  for igene in [0,1,2,3,4,5,6,8,9,10,13,11,12]:
   for imut in range(0,len(MT[igene])):
    labelcounter = labelcounter+1
    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 iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
      allmutvals.append([0]*len(thesemutvars))
    for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
      for imutvar in range(0,len(MT[igene][imut])):
        if imutvar==0:
          allmutvals[iallmutval][imutvar] = MT[igene][imut][imutvar][1][iallmutval%nVals[imutvar]]
        else:
          allmutvals[iallmutval][imutvar] = MT[igene][imut][imutvar][1][(iallmutval/cumprodnVals[imutvar-1])%nVals[imutvar]]
      
    for iallmutval in range(0,cumprodnVals[len(MT[igene][imut])-1]):
      counter = counter+1
      #print str(DataAllAll[icell][igene][imut][iallmutval])
      #if igene != 13:
      #  unpicklefile = open('../haymod3/steadystate2_cs'+str(icell)+'_'+str(igene)+'_'+str(imut)+'_'+str(iallmutval)+'.sav', 'r')
      #else:
      #  unpicklefile = open('steadystate2_cs'+str(icell)+'_'+str(igene)+'_'+str(imut)+'_'+str(iallmutval)+'.sav', 'r')
      #unpickledlist = pickle.load(unpicklefile)
      #unpicklefile.close()

      iters = [0, 2, 5, 6, 8]
      yplus = [0, 1, 2, 0, 1]
      xplus = [0, 0, 0, 0.3, 0.3]
      for iiter in range(0,len(iters)):
        iter = iters[iiter]
        thisy = [x*1.1 for x in DataAllAll[icell][igene][imut][iallmutval][iiter]]
        firstabovethree = -1
        lastabovethree = -1
        for iy in range(0,len(thisy)):
          if thisy[iy] > 3 and firstabovethree == -1:
            firstabovethree = iy
          if thisy[iy] > 3:
            lastabovethree = iy
        if firstabovethree == -1:
          thisRange = [nan,nan]
        else:
          xplusthis1 = 2.0*(3.0-thisy[firstabovethree-1])/(thisy[firstabovethree]-thisy[firstabovethree-1])
          xplusthis2 = 2.0*(3.0-thisy[lastabovethree])/(thisy[lastabovethree+1]-thisy[lastabovethree])
          thisRange = [PPIdts[firstabovethree-1]+xplusthis1,PPIdts[lastabovethree]+xplusthis2]
        
        if igene==0 and imut==0 and iallmutval==0 and iiter < 3:
          axarr.plot([-2,-2], [x+yplus[iiter]*DI for x in range_control], 'b-',color='#0000FF')
          axarr.plot([-1,98], [x+yplus[iiter]*DI for x in [range_control[0], range_control[0]]], 'k-',color='#AADDFF')
          axarr.plot([-1,98], [x+yplus[iiter]*DI for x in [range_control[1], range_control[1]]], 'k-',color='#AADDFF')
        if iter >= 0:
          thisCoeff = coeffCoeffs[iter][0]*theseCoeffs[iallmutval] + coeffCoeffs[iter][0]*(1.0 - 0.5*theseCoeffs[iallmutval])
        else:
          thisCoeff = 0
        print "iter="+str(iter)+", thisCoeff="+str(thisCoeff)
          
        mutText = ""
        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('off') > -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)
            if kmutvar < len(mutvars)-1:
              mutText = mutText + ", "
        print mutText

        axarr.plot([xplus[iiter]+counter,xplus[iiter]+counter], [x+yplus[iiter]*DI for x in thisRange], styles[iter],color=cols[iter])
        #if igene==0 and imut==0 and iallmutval==0 and iiter == 0:
        axarr.set_xlim([-4,150])
        axarr.set_xticks([])
        #axarr.set_ylim([0.000185+0.000014,0.00039+0.000014])
        #axarr.set_ylim([0.000105+0.000014,0.00039+0.000014])
        #axarr.set_yticks([min(Casoma_control),max(Casoma_control),min(Casoma_control)+DI,max(Casoma_control)+DI,min(Casoma_control)+2*DI,max(Casoma_control)+2*DI,0.000275+2*DI,0.0003+2*DI,0.000325+2*DI])
        for tick in axarr.yaxis.get_major_ticks():
          tick.label.set_fontsize(fs)
        labels = ['','','','','','','%0.3f' % 0.275,'%0.3f' % 0.3,'%0.3f' % 0.325]
        #for itick in range(0,3):
        #  labels[itick*2] = '%0.3f' % (1000*min(Casoma_control))
        #  labels[itick*2+1] = '%0.3f' % (1000*max(Casoma_control))
        #axarr.set_yticklabels(labels)
    axarr.text(counter-0.5*cumprodnVals[len(MT[igene][imut])-1]+labelxplus[labelcounter], 0.000225+0.000001*labelyplus[labelcounter], genelabels[labelcounter], {},rotation=90,fontsize=fs)

    counter = counter+1
   counter = counter+1
  axarr.text(-2.5, 0.000229, 'control', {},rotation=90,fontsize=fs)
  y1=0.00021+0.000014
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000002,y1+0.000004],'k-');
  thisline[0].set_clip_on(False)
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000000,y1+0.000002],'k-');
  thisline[0].set_clip_on(False)
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000001,y1+0.000003],'k-',color='#FFFFFF',zorder=100,linewidth=2.0);
  thisline[0].set_clip_on(False)
  y1=0.000245+0.000014
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000002,y1+0.000004],'k-');
  thisline[0].set_clip_on(False)
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000000,y1+0.000002],'k-');
  thisline[0].set_clip_on(False)
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000001,y1+0.000003],'k-',color='#FFFFFF',zorder=100,linewidth=2.0);
  thisline[0].set_clip_on(False)
  y1=0.000275+0.000014
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000002,y1+0.000004],'k-');
  thisline[0].set_clip_on(False)
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000000,y1+0.000002],'k-');
  thisline[0].set_clip_on(False)
  thisline = axarr.plot([-4.6,-3.4],[y1+0.000001,y1+0.000003],'k-',color='#FFFFFF',zorder=100,linewidth=2.0);
  thisline[0].set_clip_on(False)
  axarr.set_ylabel("PPI window span")
  
  f.savefig("ppiranges_cs"+str(icell)+".eps")
  
  

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