# drawfig3
# A script for plotting the steady-state firing properties
#
# The input code for the hoc-interface is based on BAC_firing.hoc by Etay Hay (2011)
#
# Tuomo Maki-Marttunen, Jan 2015
# (CC BY)
from neuron import h
import matplotlib
matplotlib.use('Agg')
from pylab import *
import mytools
import pickle
useLatex = False
if useLatex:
tlabel = '$t$ (ms)'
Vmlabel = '$V_m$ (mV)'
xlabel_Ca = '[Ca$^{2+}$] ($\upmu$M)'
ylabel_Ca = '$d$[Ca$^{2+}$]/$dt$ ($\upmu$M/ms)'
else:
tlabel = 't (ms)'
Vmlabel = 'V_m (mV)'
xlabel_Ca = '[Ca2+] (uM)'
ylabel_Ca = 'd[Ca2+]/dt (uM/ms)'
import mutation_stuff
MT = mutation_stuff.getMT()
geneNames = mutation_stuff.getgenenames()
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.sav', 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
theseCoeffsAllAll = unpickledlist[0]
theseMutValsAllAll = unpickledlist[2]
styles = ['b-','b-','b-','b-','b-','b-','b-','b-','b-','b-']
cols = ['#444444','#012345','#aa00aa','#bbaa00','#ee6600','#ff0000', '#009999','#772277','#00cc00']
col_control = '#2222ff'
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]]
lw = 0.6
fs = 12
v0 = -80
ca0 = 0.0001
proximalpoint = 400
distalpoint = 620
variants = [[0,1,0],[1,2,14],[3,0,1],[6,1,0],[8,0,0],[11,0,0]]
f, axarr25 = plt.subplots(2, 5)
for iy in range(0,2):
for ix in range(0,3):
axarr25[iy,ix+2].set_position([0.42+0.19*ix, 0.1+0.4*(1-iy), 0.19, 0.34])
axarr25[iy,0].set_position([0.1, 0.1+0.4*(1-iy), 0.19, 0.34])
axarr25[iy,1].set_position([0.17, 0.16+0.4*(1-iy), 0.105, 0.14])
axarr = [axarr25[0,2],axarr25[0,3],axarr25[0,4],axarr25[1,2],axarr25[1,3],axarr25[1,4]]
axtimecourse = [axarr25[0,0],axarr25[1,0]]
axzoom = [axarr25[0,1],axarr25[1,1]]
for ivar in range(0,len(variants)):
icell = 0
theseCoeffsAll = theseCoeffsAllAll[icell]
morphology_file = "morphologies/cell"+str(icell+1)+".asc"
biophys_file = "models/L5PCbiophys3.hoc"
template_file = "models/L5PCtemplate.hoc"
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+"""\")
access L5PC.soma
objref st1,sl,tvec
L5PC.soma st1 = new IClamp(0.5)
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]
objref vsoma, vdend, vdend2, cadend, cadend2, casoma
vsoma = new Vector()
casoma = new Vector()
vdend = new Vector()
cadend = new Vector()
vdend2 = new Vector()
cadend2 = new Vector()
L5PC.soma cvode.record(&v(0.5),vsoma,tvec)
L5PC.soma cvode.record(&cai(0.5),casoma,tvec)
L5PC.apic[siteVec[0]] cvode.record(&v(siteVec[1]),vdend,tvec)
L5PC.apic[siteVec[0]] cvode.record(&cai(siteVec[1]),cadend,tvec)
sl = new List()
sl = L5PC.locateSites("apic","""+str(proximalpoint)+""")
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]
L5PC.apic[siteVec[0]] cvode.record(&v(siteVec[1]),vdend2,tvec)
L5PC.apic[siteVec[0]] cvode.record(&cai(siteVec[1]),cadend2,tvec)
""") #"""
igene = variants[ivar][0]
imut = variants[ivar][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]]
iallmutval = variants[ivar][2]
iters = [0, 2, 6, 8, -1]
for iiter in range(0,len(iters)):
iter = iters[iiter]
if iter >= 0:
thiscol = cols[iter]
else:
thiscol = col_control
if iter >= 0:
thisCoeff = coeffCoeffs[iter][0]*theseCoeffs[iallmutval] + coeffCoeffs[iter][1]*(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('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 + "+" + "{0:.3f}".format(mutvals*thisCoeff) +" mV"
elif kmutvar==0:
mutText = mutText + "{0:.3f}".format(mutvals*thisCoeff) +" mV"
else:
newVal = [x*(mutvals**thisCoeff) for x in defVals[mutvar]]
if kmutvar==0:
mutText = mutText + "*" + "{0:.3f}".format(mutvals**thisCoeff)
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 "newVal="+str(newVal[0])+","+str(newVal[1])
print geneNames[igene]+", iter="+str(iter)+", mutText: "+mutText
print mutText
if iter==-1:
filename = 'fig3_cs'+str(icell)+'_control.sav'
else:
filename = 'fig3_cs'+str(icell)+'_ivar'+str(ivar)+'_iter'+str(iter)+'.sav'
try: # If the simulation has already been made, don't bother rerun it
unpicklefile = open(filename, 'r')
unpickledlist = pickle.load(unpicklefile)
unpicklefile.close()
times = unpickledlist[0]
Vsoma = unpickledlist[1]
Casoma = unpickledlist[2]
spikes = unpickledlist[3]
except:
tstop = 4000.0
squareAmp = 1.2
squareDur = 3800.0
h("""
tstop = """+str(tstop)+"""
v_init = """+str(v0)+"""
cai0_ca_ion = """+str(ca0)+"""
st1.amp = """+str(squareAmp)+"""
st1.del = 200
st1.dur = """+str(squareDur)+"""
""")
h.init()
h.run()
times=np.array(h.tvec)
Vsoma=np.array(h.vsoma)
Casoma=np.array(h.casoma)
spikes = mytools.spike_times(times,Vsoma,-35,-45)
picklelist = [times,Vsoma,Casoma,spikes]
file = open(filename, 'w')
pickle.dump(picklelist,file)
file.close()
spTimesThisCoeff = spikes[:]
nSpikes1 = len(spikes)
if nSpikes1 > 5:
spts = spikes[nSpikes1-3:nSpikes1]
istart = next((i for i,x in enumerate(times) if x > spts[0]))
iend = next((i for i,x in enumerate(times) if x > spts[1]))+4
nsteps = iend-istart-1
tdiff = [y-x for x,y in zip(times[istart:iend-1],times[istart+1:iend])]
cadiff = [y-x for x,y in zip(Casoma[istart:iend-1],Casoma[istart+1:iend])]
caderiv1 = [y/x for x,y in zip(tdiff[0:nsteps-1],cadiff[0:nsteps-1])]
caderiv2 = [y/x for x,y in zip(tdiff[1:nsteps],cadiff[1:nsteps])]
caderiv = [(x+y)/2.0 for x,y in zip(caderiv1,caderiv2)]
axarr[ivar].plot([1000.0*x for x in Casoma[istart+1:iend-1]], [1000.0*x for x in caderiv], color=thiscol, linewidth=lw)
if ivar==0: # Draw the membrane potential and [Ca] time course for CACNA1C variants
axtimecourse[0].plot(times,Vsoma, color=thiscol,linewidth=lw)
axtimecourse[1].plot(times,[1000.0*x for x in Casoma], color=thiscol,linewidth=lw)
axzoom[0].plot(times,Vsoma, color=thiscol,linewidth=lw)
axzoom[1].plot(times,[1000.0*x for x in Casoma], color=thiscol,linewidth=lw)
axarr[ivar].set_title(geneNames[igene],fontsize=fs+2.4)
axarr[ivar].set_xticks([0.23,0.24,0.25])
axarr[ivar].set_xlim([0.228,0.258])
axarr[ivar].set_yticks([0,0.002,0.004,0.006])
axarr[ivar].set_ylim([-0.0006,0.0073])
if ivar < 3:
axarr[ivar].set_xticklabels(['','',''])
else:
axarr[ivar].set_xlabel(xlabel_Ca)
if ivar % 3 > 0:
axarr[ivar].set_yticklabels(['','',''])
else:
axarr[ivar].set_ylabel(ylabel_Ca)
for tick in axarr[ivar].yaxis.get_major_ticks()+axarr[ivar].xaxis.get_major_ticks():
tick.label.set_fontsize(fs)
for ix in range(0,5):
for iy in range(0,2):
axarr25[iy,ix].xaxis.set_ticks_position('bottom')
axarr25[iy,ix].yaxis.set_ticks_position('left')
axtimecourse[0].set_xticks([200,400,600])
axtimecourse[0].set_xticklabels(['0','200','400'])
axtimecourse[0].set_xlim([190,700])
axtimecourse[0].set_yticks([-100,-50,0])
axtimecourse[0].set_ylim([-300,40])
axtimecourse[0].set_ylabel(Vmlabel)
axtimecourse[1].set_xticks([200,400,600])
axtimecourse[1].set_xticklabels(['0','200','400'])
axtimecourse[1].set_xlim([190,700])
axtimecourse[1].set_yticks([0.1,0.15,0.2,0.25])
axtimecourse[1].set_ylim([0.09,0.27])
axtimecourse[1].set_ylabel(xlabel_Ca)
axtimecourse[1].set_xlabel(tlabel)
axzoom[0].set_xticks([3600,3800])
axzoom[0].set_xticklabels(['3400','3600'])
axzoom[0].set_xlim([3580,3862])
axzoom[0].set_yticks([-50,0])
axzoom[0].set_ylim([-70,25])
axzoom[1].set_xticks([3600,3800])
axzoom[1].set_xticklabels(['3400','3600'])
axzoom[1].set_xlim([3580,3862])
axzoom[1].set_yticks([0.24,0.25])
axzoom[1].set_ylim([0.234,0.255])
f.text(0.01, 0.81, 'A', fontsize=33)
f.text(0.01, 0.41, 'B', fontsize=33)
f.text(0.31, 0.81, 'C', fontsize=33)
if useLatex:
params = {'text.latex.preamble': [r"\usepackage{upgreek}"],
'text.usetex': True}
plt.rcParams.update(params)
f.savefig("figure3.eps")