Simulations of modulation of HCN channels in L5PCs (Mäki-Marttunen and Mäki-Marttunen, 2022)

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Accession:267293
"... In this work, we build upon existing biophysically detailed models of thick-tufted layer V pyramidal cells and model the effects of over- and under-expression of Ih channels as well as their neuromodulation by dopamine (gain of Ih function) and acetylcholine (loss of Ih function). We show that Ih channels facilitate the action potentials of layer V pyramidal cells in response to proximal dendritic stimulus while they hinder the action potentials in response to distal dendritic stimulus at the apical dendrite. We also show that the inhibitory action of the Ih channels in layer V pyramidal cells is due to the interactions between Ih channels and a hot zone of low voltage-activated Ca2+ channels at the apical dendrite. Our simulations suggest that a combination of Ih-enhancing neuromodulation at the proximal apical dendrite and Ih-inhibiting modulation at the distal apical dendrite can increase the layer V pyramidal excitability more than any of the two neuromodulators alone..."
Reference:
1 . Mäki-Marttunen T, Mäki-Marttunen V (2022) Excitatory and inhibitory effects of HCN channel modulation on excitability of layer V pyramidal cells Plos Comp Biol [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 layer 5 pyramidal cell;
Channel(s):
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Gene(s):
Transmitter(s): Acetylcholine; Dopamine; Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Neuromodulation;
Implementer(s): Maki-Marttunen, Tuomo [tuomomm at uio.no];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; Acetylcholine; Dopamine; Gaba; Glutamate;
from pylab import *
import scipy.io
import pickle
from os.path import exists
from matplotlib.collections import PatchCollection
import scipy.stats

def mystr(x):
  mystr = str(x)
  if '000000' in mystr or '999999' in mystr:
    for q in range(7,0,-1):
      mystr = ('{:.'+str(q)+'f}').format(x)
      ilast = len(mystr)-1
      if 'e' in mystr:
        ilast = mystr.find('e') - 1
      if mystr[ilast] != '0':
        return mystr
  return mystr
def myscistr(x):
  mystr = '{:e}'.format(x)
  if '0000' in mystr or '9999' in mystr:
    for q in range(7,0,-1):
      mystr = ('{:.'+str(q)+'e}').format(x)
      ilast = mystr.find('e') - 1
      if mystr[ilast] != '0':
        return mystr
  return mystr

def discontlog(ax,x,y,width=18,height=1.05,col='#000000'):
  ax.plot([x-width/2,x+width/2],[y/sqrt(height),y*sqrt(height)],'k-',lw=2.3,clip_on=False,color=col)
  ax.plot([x-width,x+width],[y/height,y*height],'w-',lw=1.0,clip_on=False,zorder=100)

f,axarr = subplots(3,1)

axarr[0].set_position([0.3,0.53,0.4,0.4])
axarr[1].set_position([0.1,0.06,0.4,0.4])
axarr[2].set_position([0.52,0.06,0.4,0.4])
for iax in range(0,3):
  for tick in axarr[iax].xaxis.get_major_ticks() + axarr[iax].yaxis.get_major_ticks():
    tick.label.set_fontsize(3.5)
    axarr[iax].spines['top'].set_visible(False)
    axarr[iax].spines['right'].set_visible(False)
    axarr[iax].get_xaxis().tick_bottom()
    axarr[iax].get_yaxis().tick_left()

colslope = 2e-5

#Apical, givendists, Almog+Hay:
dist1s = [200,300,400,500,600,700,800,900,1000,1100,1200,1300]
treename = 'apic'
Ihcoeffs = [0.0,1.0]

for imodel in range(0,3):
 minmaxes = [inf,-inf]
 coeffs_saved = [[],[]]
 for idist1 in range(0,len(dist1s)):
  dist1 = dist1s[idist1]
  for idist2 in range(0,len(dist1s)):
    dist2 = dist1s[idist2]
    threshEcons_thisdist2 = []
    for iIhcoeff in range(0,2):
      Ihcoeff = Ihcoeffs[iIhcoeff]
      Ihmod = 0.0
      if imodel > 0 and Ihcoeff == 0.0:
        Ihmod = 10.0 if imodel == 1 else -10.0
      foundOne = 0
      threshEcons = []
      for myseed in range(1,41):
        if imodel == 0:
          filename = 'ffthreshs/ffthreshs_Ihcoeff'+str(Ihcoeff)+'_apicalCaLVAHay_0.003_100.0_dists585-985_'+treename+str(dist1)+'-'+str(dist2)+'_seed'+str(myseed)+'.sav'
        else:
          if Ihcoeff == 0:
            filename = '../modulhcn_hay/ffthreshs/ffthreshs_Ihmod'+str(Ihmod)+'_'+treename+str(dist1)+'-'+str(dist2)+'_seed'+str(myseed)+'.sav'
          else:
            filename = '../modulhcn_hay/ffthreshs/ffthreshs_Ihcoeff1.0_'+treename+str(dist1)+'-'+str(dist2)+'_seed'+str(myseed)+'.sav'
        if exists(filename):
          unpicklefile = open(filename,'rb')
          unpickledlist = pickle.load(unpicklefile)
          unpicklefile.close()
          threshEcons.append(unpickledlist[0][2])
          foundOne = 1
          print('loaded '+filename)
      #if not foundOne:
      #  print(filename+' does not exist')
      threshEcons_thisdist2.append(threshEcons[:])

      if len(threshEcons) == 0:
        continue
      c = tanh(mean(threshEcons[:])/colslope)
      minmaxes = [min(minmaxes[0],mean(threshEcons[:])),max(minmaxes[1],(mean(threshEcons[:]) if mean(threshEcons[:]) < 0.0999 else -inf))]

      myhex = hex(255-int(255*c))
      if len(myhex) < 3:
        mycol = '#000000'
      elif len(myhex) < 4:
        mycol = '#'+'0'+myhex[2]+'0'+myhex[2]+'0'+myhex[2]
      elif len(myhex) > 4:
        mycol = '#000000'
      else:
        mycol = '#'+myhex[2:]+myhex[2:]+myhex[2:]

      if iIhcoeff == 0:
        polygon = Polygon(array([[idist1,idist1+1,idist1],[idist2,idist2,idist2+1]]).T, True) #lower left triangle modulated
      else:
        polygon = Polygon(array([[idist1,idist1+1,idist1+1],[idist2+1,idist2,idist2+1]]).T, True) #upper right triangle control
      p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
      p.set_facecolor(mycol); p.set_edgecolor('none')
      axarr[imodel].add_collection(p)
    if len(threshEcons_thisdist2) > 1 and len(threshEcons_thisdist2[0]) > 1 and len(threshEcons_thisdist2[1]) > 1:
      s1 = mean(threshEcons_thisdist2[0])
      s2 = mean(threshEcons_thisdist2[1])
      if s1 == s2:
        mycol = '#808080'
      elif s1 > s2: # more spiking with Ih than without
        c = tanh((s1/s2 - 1)/2)
        #print('c = '+str(c))
        myhex = hex(200-int(200*c))
        if len(myhex) < 3:
          mycol = '#000000'
        elif len(myhex) < 4:
          mycol = '#ff'+'0'+myhex[2]+'0'+myhex[2]
        elif len(myhex) > 4:
          mycol = '#ff0000'
        else:
          mycol = '#ff'+myhex[2:]+myhex[2:]
        coeffs_saved[0].append(s1/s2)
      else: # more spiking without Ih than without
        c = tanh((s2/s1 - 1)/2)
        #print('c = '+str(c))
        myhex = hex(200-int(200*c))
        if len(myhex) < 4:
          mycol = '#0'+myhex[2]+'0'+myhex[2]+'ff'
        elif len(myhex) > 4:
          mycol = '#0000ff'
        else:
          mycol = '#'+myhex[2:]+myhex[2:]+'ff'
        coeffs_saved[1].append(s1/s2)
      #print(mycol)
      #print(myhex)
      #print('s1 = '+str(s1)+', s2 = '+str(s2))
      pval = scipy.stats.ranksums(threshEcons_thisdist2[0], threshEcons_thisdist2[1])[1]
      polygon = Polygon(array([[idist2+1,idist2+1,idist2,idist2],[idist1,idist1+1,idist1+1,idist1]]).T, True)
      p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
      p.set_facecolor(mycol); p.set_edgecolor('none')
      axarr[imodel].add_collection(p)
      if pval < 0.05/66:
        axarr[imodel].plot(idist2+0.5,idist1+0.5,'k*',lw=0.5,mew=0.5,ms=2.0)
 print('minmaxes = '+str(minmaxes))
 print('coeffs_saved = '+str(unique(coeffs_saved[0]))+' and '+str(unique(coeffs_saved[1])))


axnew = f.add_axes([0.16,0.49,0.05,0.49])
axnew2 = f.add_axes([0.7,0.49,0.05,0.49])
zs = [2.0e-6*i for i in range(0,21)]
for iz in range(0,len(zs)):
  polygon = Polygon(array([[1,2,2,1],[iz,iz,iz+1,iz+1]]).T, True) 
  c = tanh(zs[iz]/colslope)
  
  myhex = hex(int(255-255*c))
  if len(myhex) < 4:
    mycol = '#'+'0'+myhex[2]+'0'+myhex[2]+'0'+myhex[2]
  elif len(myhex) > 4:
    mycol = '#000000'
  else:
    mycol = '#'+myhex[2:]+myhex[2:]+myhex[2:]
  print('myhex='+myhex)
  p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
  p.set_facecolor(mycol); p.set_edgecolor('none')
  axnew.add_collection(p)
  if iz < len(zs)-1:
    axnew.text(0.8,iz+0.5,myscistr(1e3*zs[iz]),fontsize=4,ha='right',va='center') # convert from uS to nS
  else:
    axnew.text(0.8,iz+0.5,'$\geq$0.04',fontsize=4,ha='right',va='center')
axnew.set_ylim([0,21])
axnew.set_xlim([0,2])
axnew.get_xaxis().set_visible(False)
axnew.get_yaxis().set_visible(False)
for q in ['top','bottom','left','right']:
  axnew.spines[q].set_visible(False)

zs = [1.1]+[1.0+0.5*i for i in range(1,10)]
for iz in range(0,len(zs)):
  polygon = Polygon(array([[1,2,2,1],[iz+1,iz+1,iz+2,iz+2]]).T, True) 
  polygon2 = Polygon(array([[1,2,2,1],[-iz,-iz,-iz-1,-iz-1]]).T, True) 
  c = tanh((zs[iz]-1)/2)
  myhex = hex(200-int(200*c))
  print('myhex='+myhex)
  if len(myhex) < 3:
    mycol = '#000000'
  elif len(myhex) < 4:
    mycol = '#ff'+'0'+myhex[2]+'0'+myhex[2]
  elif len(myhex) > 4:
    mycol = '#ff0000'
  else:
    mycol = '#ff'+myhex[2:]+myhex[2:]

  if len(myhex) < 4:
    mycol2 = '#0'+myhex[2]+'0'+myhex[2]+'ff'
  elif len(myhex) > 4:
    mycol2 = '#0000ff'
  else:
    mycol2 = '#'+myhex[2:]+myhex[2:]+'ff'

  p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
  p.set_facecolor(mycol); p.set_edgecolor('none')
  axnew2.add_collection(p)
  if iz < len(zs)-1:
    axnew2.text(0.8,iz+1.5,mystr(zs[iz]),fontsize=4,ha='right',va='center')
  else:
    axnew2.text(0.8,iz+1.5,'>5',fontsize=4,ha='right',va='center')

  p = PatchCollection([polygon2], cmap=matplotlib.cm.jet)
  p.set_facecolor(mycol2); p.set_edgecolor('none')
  axnew2.add_collection(p)
  if iz < len(zs)-1:
    axnew2.text(0.8,-iz-0.5,mystr(zs[iz]),fontsize=4,ha='right',va='center')
  else:
    axnew2.text(0.8,-iz-0.5,'>5',fontsize=4,ha='right',va='center')

polygon = Polygon(array([[1,2,2,1],[0,0,1,1]]).T, True) 
p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
p.set_facecolor('#808080'); p.set_edgecolor('none')
axnew2.add_collection(p)
axnew2.text(0.5,0.5,'n/a',fontsize=4,ha='center',va='center')

axnew2.set_ylim([-11,12])
axnew2.set_xlim([0,2])
axnew2.get_xaxis().set_visible(False)
axnew2.get_yaxis().set_visible(False)
for q in ['top','bottom','left','right']:
  axnew2.spines[q].set_visible(False)

axnew2.text(2.2,3.5,'Threshold larger for $I_h$-modulated',fontsize=4,color='#FF0000',ha='left',va='bottom',rotation=90,clip_on=False)
axnew2.text(2.2,-1.5,'Threshold smaller for $I_h$-modulated',fontsize=4,color='#0000FF',ha='left',va='top',rotation=90,clip_on=False)

for iax in range(0,3):
  axarr[iax].set_xticks([0.5+x for x in range(0,len(dist1s))])
  axarr[iax].set_xticklabels([str(d) for d in dist1s],fontsize=4,rotation=20)
  axarr[iax].set_yticks([0.5+x for x in range(0,len(dist1s))])
  if iax < 2: 
    axarr[iax].set_yticklabels([str(d) for d in dist1s],fontsize=4,rotation=20)
  else:
    axarr[iax].set_yticklabels([])

  #for ix in range(0,2):
  #  axarr[0,ix].set_xticks([0.5+x for x in range(0,len(dist1s))])
  #  axarr[0,ix].set_xticklabels([str(d) for d in dist1s],fontsize=4)
  #  axarr[0,ix].set_yticks([0.5+x for x in range(0,len(dist2s))])
  #  axarr[0,ix].set_yticklabels([str(d) for d in dist2s],fontsize=4)
  #  axarr[0,ix].set_xlim([0,len(dist1s)])
  #  axarr[0,ix].set_ylim([0,len(dist2s)])

for iax in range(0,3):
  pos = axarr[iax].get_position()
  f.text(pos.x0 - 0.05, pos.y1 - 0.01, chr(ord('A')+iax), fontsize=9)

f.savefig("figS4.eps")

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