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VB6_simulation_vclamp.py
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VB6_simulation_vclamp.py
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# "Biophysical modeling of the whole-cell dynamics of C. elegans motor and interneurons families"
# M. Nicoletti et al. PloS ONE, 19(3): e0298105.
# https://doi.org/10.1371/journal.pone.0298105
def VB6_simulation_vc(gVB6_scaled,vstart,vstop,ns):
# lista canali da cenGen tramite ricerca per geni
# calcio e kcnl fisstao con i valori di t15.ode
from neuron import h,gui
import numpy
import math
from neuron import h,gui
import numpy
import math
surf=524.64e-8 # surface in cm^2 form neuromorpho VB6L
vol=58.54e-12 # total volume
L=math.sqrt(surf/math.pi)
rsoma=L*1e4
cm_uFcm2=1
soma=h.Section(name="soma")
soma.L=rsoma
soma.diam=rsoma
soma.Ra=100
soma.cm=gVB6_scaled[15]
h.psection(sec=soma)
soma.insert('slo2egl19')
soma.insert('slo1egl19')
soma.insert('slo2unc2')
soma.insert('slo1unc2')
soma.insert('slo2iso')
soma.insert('slo1iso')
soma.insert('egl19')
soma.insert('unc2')
soma.insert('cca1')
soma.insert('irk')
soma.insert('shk1')
soma.insert('leak')
soma.insert('nca')
soma.insert('cadiff')
for seg in soma:
seg.slo1egl19.gbar=gVB6_scaled[0]
seg.slo2egl19.gbar = gVB6_scaled[1]
seg.slo1unc2.gbar=gVB6_scaled[2]
seg.slo2unc2.gbar = gVB6_scaled[3]
seg.slo1iso.gbar = gVB6_scaled[4]
seg.slo2iso.gbar=gVB6_scaled[5]
seg.egl19.gbar=gVB6_scaled[6]
seg.unc2.gbar=gVB6_scaled[7]
seg.cca1.gbar=gVB6_scaled[8]
seg.irk.gbar=gVB6_scaled[9]
seg.shk1.gbar=gVB6_scaled[10]
seg.nca.gbar=gVB6_scaled[11]
seg.leak.gbar=gVB6_scaled[12]
seg.leak.e=gVB6_scaled[13]
seg.slo2iso.c2=gVB6_scaled[14]
seg.eca=60
seg.ek=-80
stim=h.VClamp(soma(0.5))
dir(stim)
simdur = 1700
stim.amp[0]=-60
stim.amp[1]=-110
stim.amp[2]=-60
stim.dur[0]=1025
stim.dur[1]=600
stim.dur[2]=100
ik_vec = h.Vector()
ica_vec=h.Vector()
inca_vec=h.Vector()
ileakVB6_vec=h.Vector()
t_vec = h.Vector()
#curr_shl1_vec=h.Vector()
# Time stamp vector
ik_vec.record(soma(0.5)._ref_ik)
ica_vec.record(soma(0.5)._ref_ica)
inca_vec.record(soma(0.5)._ref_i_nca)
ileakVB6_vec.record(soma(0.5)._ref_i_leak)
# curr_shl1_vec.record(soma(0.5)._ref_curr_shl1)
t_vec.record(h._ref_t)
ref_ik=[]
ref_ica=[]
ref_t=[]
ref_inca=[]
ref_ileakVB6=[]
#ref_curr_shl1=[]
for i in numpy.linspace(start=vstart, stop=vstop, num=ns):
stim.amp[1]=i
h.tstop=simdur
h.dt=0.01
h.finitialize(-60)
h.run()
#time
ref_t_vec=numpy.zeros_like(t_vec)
t_vec.to_python(ref_t_vec)
ref_t.append(ref_t_vec)
# potassium current
ref_ik_vec=numpy.zeros_like(ik_vec)
ik_vec.to_python(ref_ik_vec)
ref_ik.append(ref_ik_vec)
# shl1
#ref_curr_shl1_vec=numpy.zeros_like(curr_shl1_vec)
#curr_shl1_vec.to_python(ref_curr_shl1_vec)
#ref_curr_shl1.append(ref_curr_shl1_vec)
#calcium currents
ref_ica_vec=numpy.zeros_like(ica_vec)
ica_vec.to_python(ref_ica_vec)
ref_ica.append(ref_ica_vec)
# NCA currents
ref_inca_vec=numpy.zeros_like(inca_vec)
inca_vec.to_python(ref_inca_vec)
ref_inca.append(ref_inca_vec)
# LEAKAGE current
ref_ileakVB6_vec=numpy.zeros_like(ileakVB6_vec)
ileakVB6_vec.to_python(ref_ileakVB6_vec)
ref_ileakVB6.append(ref_ileakVB6_vec)
# total current calculation
itot=[]
#itot=map(sum, zip(ref_ik,ref_ica,ref_inca,ref_ileakVB6))
itot=map(sum, zip(ref_ik,ref_ica,ref_ileakVB6,ref_inca))
current=numpy.array(list(itot))
inorm=current*1e9*surf #total current in pA
#time array
time1=numpy.array(ref_t)
resc_ind=numpy.where(time1[1,:]>=1000)
resc_min=numpy.amin(resc_ind)
resc_max=numpy.amax(resc_ind)
itot_normalized=inorm[:,resc_min:resc_max]
time=time1[:,resc_min:resc_max]-1000
## CALCULATION OF STEADY-STATE CURRENT-VOLATGE RELATION
ind=numpy.where(numpy.logical_and(time[0]>=600, time[0]<=625))
ind_max=numpy.amax(ind)
ind_min=numpy.amin(ind)
iv=numpy.mean(itot_normalized[:,ind_min:ind_max],axis=1)
# CALCULATION OF PEAK CURRENT-VOLTAGE RELATION (as in Ramot et al 2008)
ind2=numpy.where(numpy.logical_and(time[0]>=25, time[0]<=100))
ind2_max=numpy.amax(ind2)
ind2_min=numpy.amin(ind2)
iv_peak=numpy.amax(itot_normalized[:,ind2_min:ind2_max])
iv_peak=[]
#for j in range(ns):
# peak=numpy.amax(itot_normalized[j,ind2_min:ind2_max])
# iv_peak.append(peak)
#iv_peak=numpy.array(list(iv_peak))
for j in range(ns):
if j<=6:
peak=numpy.amin(itot_normalized[j,ind2_min:ind2_max])
else:
peak=numpy.amax(itot_normalized[j,ind2_min:ind2_max])
iv_peak.append(peak)
return itot_normalized, time, iv_peak, iv