Multitarget pharmacology for Dystonia in M1 (Neymotin et al 2016)

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Accession:189154
" ... We developed a multiscale model of primary motor cortex, ranging from molecular, up to cellular, and network levels, containing 1715 compartmental model neurons with multiple ion channels and intracellular molecular dynamics. We wired the model based on electrophysiological data obtained from mouse motor cortex circuit mapping experiments. We used the model to reproduce patterns of heightened activity seen in dystonia by applying independent random variations in parameters to identify pathological parameter sets. ..."
Reference:
1 . Neymotin SA, Dura-Bernal S, Lakatos P, Sanger TD, Lytton WW (2016) Multitarget Multiscale Simulation for Pharmacological Treatment of Dystonia in Motor Cortex. Front Pharmacol 7:157 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Molecular Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex layer 4 neuron; Neocortex layer 2-3 interneuron; Neocortex layer 4 interneuron; Neocortex layer 5 interneuron; Neocortex layer 6a interneuron;
Channel(s): I A; I h; I_SERCA; Ca pump; I K,Ca; I Calcium; I L high threshold; I T low threshold; I N; I_KD; I M; I Na,t;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; mGluR;
Gene(s): HCN1;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Oscillations; Activity Patterns; Beta oscillations; Reaction-diffusion; Calcium dynamics; Pathophysiology; Multiscale;
Implementer(s): Neymotin, Sam [Samuel.Neymotin at nki.rfmh.org]; Dura-Bernal, Salvador [salvadordura at gmail.com];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; GabaA; GabaB; AMPA; mGluR; I Na,t; I L high threshold; I N; I T low threshold; I A; I M; I h; I K,Ca; I Calcium; I_SERCA; I_KD; Ca pump; Gaba; Glutamate;
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dystdemo
readme.txt
cagk.mod
cal.mod *
calts.mod *
can.mod *
cat.mod *
gabab.mod
h_winograd.mod
HCN1.mod
IC.mod *
icalts.mod *
ihlts.mod *
kap.mod
kcalts.mod *
kdmc.mod
kdr.mod
km.mod *
mglur.mod *
misc.mod *
MyExp2SynBB.mod *
MyExp2SynNMDABB.mod
nax.mod
stats.mod *
vecst.mod *
aux_fun.inc *
conf.py
declist.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
geom.py
ghk.inc *
grvec.hoc
init.hoc
labels.hoc
labels.py *
local.hoc *
misc.h
mpisim.py
netcfg.cfg
nqs.hoc *
nqs.py
nrnoc.hoc *
pyinit.py *
python.hoc *
pywrap.hoc *
simctrl.hoc *
simdat.py
syn.py
syncode.hoc *
vector.py *
xgetargs.hoc *
                            
import sys
from pyinit import *
from labels import *
from math import exp
h.celsius = 37
h.load_file("pywrap.hoc")
from conf import *
# determine config file name
def setfcfg ():
  fcfg = "netcfg.cfg" # default config file name
  for i in xrange(len(sys.argv)):
    if sys.argv[i].endswith(".cfg") and os.path.exists(sys.argv[i]):
      fcfg = sys.argv[i]
  return fcfg

fcfg=setfcfg() # config file name
dconf = readconf(fcfg)
taurcada = dconf['taurcada']
h.cac_hcnwino = 0.006
h.k4_hcnwino = dconf['iark4'] 
ihginc = h.ginc_hcnwino = dconf['ihginc'];
recdt = dconf['recdt']
recvdt = dconf['recvdt']
erevh = dconf['erevh']
spaceum = dconf['spaceum']
h_lambda = dconf['h_lambda']
h_gbar = dconf['h_gbar'] # for E cells
fs_h_gbar = dconf['fs_h_gbar'] # 
lts_h_gbar = dconf['lts_h_gbar'] # 
cagk_gbar = dconf['cagk_gbar'] # 
ikc_gkbar = dconf['ikc_gkbar'] # 
cabar = dconf['cabar'] # used for E cells
lts_cabar = dconf['lts_cabar']
tau1NMDAEE=15; tau2NMDAEE=150;
tau1NMDAEI=15; tau2NMDAEI=150;
nax_gbar = dconf['nax_gbar'] 
kdr_gbar = dconf['kdr_gbar'] 
kap_gbar = dconf['kap_gbar'] 
kdmc_gbar = dconf['kdmc_gbar'] 
km_gmax = dconf['km_gmax'] 
##

from syn import *

# if rdt > 0 use fixed interval for recording, else let cvode determine it
def saferecord (var, rdt):
  if rdt > 0.0:
    vrec = h.Vector(h.tstop/rdt + 1)
    vrec.record(var,rdt)
  else:
    vrec = h.Vector()
    vrec.record(var)
  return vrec
		
###############################################################################
# General Cell
###############################################################################
class Cell:
  "General cell"
  def __init__ (self,x,y,z,ID,ty):
    self.x=x
    self.y=y
    self.z=z
    self.ID=ID
    self.ty = ty
    self.snames = [] # list of section names
    self.all_sec = []
    self.add_comp('soma',True)
    self.set_morphology()
    self.set_conductances()
    self.set_synapses()
    self.set_inj()
    
  # get number of outgoing connections
  def set_morphology (self): pass			
  def set_conductances (self): pass
  def set_synapses (self): pass
  def set_inj (self): self.somaInj = h.IClamp(0.5, sec=self.soma)	
		
  def add_comp (self, name, rec):
    self.snames.append( name )
    self.__dict__[name] = h.Section()
    self.all_sec.append(self.__dict__[name])
    if rec:    # Record voltage
      self.__dict__[name+"_volt"] = saferecord(self.__dict__[name](0.5)._ref_v, recvdt)
      self.__dict__[name+"_volt"].label(name+"_volt")
      
###############################################################################
# Soma-targeting interneuron (fast-spiking Basket Cell -- Bas)
###############################################################################
class Bas (Cell):
  "Basket cell"	
  def set_morphology(self):
    total_area = 10000 # um2
    self.soma.nseg  = 1
    self.soma.cm    = 1      # uF/cm2
    diam = sqrt(total_area) # um
    L    = diam/pi  # um			
    h.pt3dclear(sec=self.soma)
    h.pt3dadd(self.x, self.y, self.z,   diam, sec=self.soma)
    h.pt3dadd(self.x, self.y, self.z+L, diam, sec=self.soma)
			
  def set_conductances(self): # Bas
    cap         = 1.0
    rall        = 150.0
    rm          = 10e3 
    Vrest       = -79.8
    p_ek          = -85.0 
    p_ena        = 55.0 
    sh_nax = 0.0
    sec = self.soma
    sec.insert('k_ion')
    sec.insert('na_ion')
    #sec.insert('ca_ion')
    sec.insert('pas') # passive     
    sec.insert('nax') # Na current      
    sec.insert('kdr') # K delayed rectifier current
    # erev
    sec.ek = p_ek # K+ current reversal potential (mV)
    sec.ena = p_ena # Na+ current reversal potential (mV)
    # passive
    sec.g_pas = 1.0/rm
    sec.Ra = rall
    sec.cm = cap
    sec.e_pas = Vrest
    # Na
    sec.gbar_nax = nax_gbar
    sec.sh_nax = sh_nax
    # KDR
    sec.gbar_kdr = kdr_gbar
    self.soma.insert('HCN1')
    self.soma(0.5).HCN1.gbar = fs_h_gbar
	   
  def set_synapses(self):
    self.somaGABAf=Synapse(sect=self.soma,loc=0.5,tau1=0.07,tau2=9.1,e=-80);#self.dSy['somaGABAf']=self.somaGABAf;
    self.somaGABAss=Synapse(sect=self.soma,loc=0.5,tau1=20,tau2=40,e=-80);#self.dSy['somaGABAss']=self.somaGABAss;
    self.somaAMPA=Synapse(sect=self.soma,loc=0.5,tau1=0.05,tau2=5.3,e=0);#self.dSy['somaAMPAf']=self.somaAMPAf;
    self.somaNMDA=SynapseNMDA(sect=self.soma,loc=0.5, tau1NMDA=tau1NMDAEI,tau2NMDA=tau2NMDAEI,r=1,e=0);
		
###############################################################################
# Dendrite-targeting interneuron (LTS Cell)
###############################################################################
class Lts (Cell):
  "LTS cell"   
  def set_morphology(self):
    total_area = 10000 # um2
    self.soma.nseg  = 1
    self.soma.cm    = 1      # uF/cm2
    diam = sqrt(total_area) # um
    L    = diam/pi  # um
    h.pt3dclear(sec=self.soma)
    h.pt3dadd(self.x, self.y, self.z,   diam, sec=self.soma)
    h.pt3dadd(self.x, self.y, self.z+L, diam, sec=self.soma)
	
  def set_conductances(self): # LTS
    cap         = 1.0
    rall        = 150.0
    rm          = 10e3 
    Vrest       = -79.8
    p_ek          = -85.0 
    p_ena        = 55.0 
    sh_nax = 0.0
    sec = self.soma
    sec.insert('k_ion')
    sec.insert('na_ion')
    sec.insert('pas') # passive     
    sec.insert('nax') # Na current      
    sec.insert('kdr') # K delayed rectifier current
    # erev
    sec.ek = p_ek # K+ current reversal potential (mV)
    sec.ena = p_ena # Na+ current reversal potential (mV)
    # passive
    sec.g_pas = 1.0/rm
    sec.Ra = rall
    sec.cm = cap
    sec.e_pas = Vrest
    # Na
    sec.gbar_nax = nax_gbar
    sec.sh_nax = sh_nax
    # KDR
    sec.gbar_kdr = kdr_gbar
    # ca-related 
    sec.insert('icalts')
    sec(0.5).icalts.gca = lts_cabar
    sec.insert('kcalts')
    sec.insert('ihlts')
    sec(0.5).ihlts.gh = lts_h_gbar
    sec.insert('calts') # calcium extrusion
    sec(0.5).calts.tau = taurcada
    
  def set_synapses(self):
    self.somaGABAf 	= Synapse(sect=self.soma, loc=0.5, tau1=0.07, tau2=9.1, e=-80)
    self.somaGABAss	= Synapse(    sect=self.soma, loc=0.5, tau1=20,	  tau2=40, e=-80)#originally for septal input
    self.somaAMPA 	= Synapse(    sect=self.soma, loc=0.5, tau1=0.05, tau2=5.3, e=0)
    self.somaNMDA 	= SynapseNMDA(sect=self.soma, loc=0.5, tau1NMDA=tau1NMDAEI, tau2NMDA=tau2NMDAEI, r=1, e=0)

LTS = Lts
FS = Bas
		
###############################################################################
# Pyramidal Cell
###############################################################################
class PyrAdr (Cell):
  "Pyramidal cell"
  def __init__(self,x,y,z,ID,ty):
    Cell.__init__(self,x,y,z,ID,ty)
    self.set_props()
    lrec = ['soma','Adend3']

  def set_morphology(self):
    self.add_comp('Bdend',True)
    self.add_comp('Adend1',False)
    self.add_comp('Adend2',False)
    self.add_comp('Adend3',True)
    self.apic = [self.Adend1, self.Adend2, self.Adend3]
    self.basal = [self.Bdend]
    sec = self.soma; sec.L = 20.0; sec.diam = 20.0
    if self.ty == E5R or self.ty == E5B or self.ty == E5P: apicL = 300.0
    else: apicL = 150.0
    #else: apicL = 300.0
    for sec in self.apic:
      sec.L = apicL; sec.diam = 2.0
    self.Bdend.L = 200.0; self.Bdend.diam = 2.0

    self.Bdend.connect(self.soma,    0, 0)
    self.Adend1.connect(self.soma,   1, 0)
    self.Adend2.connect(self.Adend1, 1, 0)
    self.Adend3.connect(self.Adend2, 1, 0)

    if spaceum > 0.0:
      for sec in self.all_sec:
        ns = int(sec.L / spaceum)
        if ns % 2 == 0: ns += 1
        sec.nseg = ns

  def set_props (self): # PYR
    Vrest       = -79.8 
    h.v_init = -60.0
    #h.v_init = -79.8 # -70 # -75 # -79.8 # Vrest # -79.8
    # passive properties
    cap         = 1.0
    rall        = 150.0
    rm          = 10e3 
    # Na, K reversal potentials calculated from
    # internal and external solutions via Nernst equation
    p_ek          = -85.0 
    p_ena        = 55.0 
    # h-current 
    #h.erev_h      = -42.0
    gbar_h      = h_gbar 
    # d-current 
    kdmc_gbar_somam = 20
    # na,k 
    sh_nax = 0.0
    gbar_nax    = nax_gbar
    nax_gbar_somam = 5
    kdr_gbar_somam = 5
    # A few kinetic params changed vis-a-vis kdr_BS.mod defaults:
    h.a0n_kdr     = 0.0075 # def 0.02
    h.nmax_kdr    = 20.0 # def 2
    sh_kap = 0.0
    kap_gbar_somam = 5
    # A few kinetic params changed from kap_BS.mod defaults:
    h.vhalfn_kap  = 35.0 # def 11
    h.nmin_kap    = 0.4 # def 0.1
    h.lmin_kap    = 5.0 # def 2
    h.tq_kap      = -45.0 # def -40
    # other ion channel parameters
    cal_gcalbar = cabar 
    can_gcanbar = cabar 
    cat_gcatbar = cabar 
    calginc = 1.0 # 2.0 - middle might need to get more but can leave out
    cal_gbar_somam = can_gbar_somam = cat_gbar_somam = 0.1
    cal_gbar_bdendm = can_gbar_bdendm = cat_gbar_bdendm = 0.25
    ikc_gbar_dendm = 0.25
    for sec in self.all_sec:
      # erev
      sec.ek = p_ek # K+ current reversal potential (mV)
      sec.ena = p_ena # Na+ current reversal potential (mV)
      # passive
      sec.g_pas = 1.0/rm
      sec.Ra = rall
      sec.cm = cap
      sec.e_pas = Vrest
      # Ih
      sec.ehwino = erevh
      for seg in sec:
        seg.hcnwino.k2 = 1e-4 # 1e-5 # 
        seg.hcnwino.ghbar = gbar_h
      # Na
      sec.gbar_nax = gbar_nax
      sec.sh_nax = sh_nax
      # KDR
      sec.gbar_kdr = kdr_gbar
      # K-A
      sec.gbar_kap = kap_gbar
      sec.sh_kap = sh_kap
    soma = self.soma
    soma.gbar_kdmc  = kdmc_gbar * kdmc_gbar_somam
    soma.gbar_nax = nax_gbar * nax_gbar_somam
    soma.gbar_kdr = kdr_gbar * kdr_gbar_somam
    soma.gbar_kap = kap_gbar * kap_gbar_somam
    soma.gkbar_ikc = ikc_gkbar
    soma.gcalbar_cal = cal_gcalbar * cal_gbar_somam
    soma.gcanbar_can = can_gcanbar * can_gbar_somam
    soma.gcatbar_cat = cat_gcatbar * cat_gbar_somam
    h.distance(0,0.5,sec=self.soma) # middle of soma is origin for distance
    for sec in self.apic:
      sec.gcalbar_cal = cal_gcalbar
      sec.gcanbar_can = can_gcanbar
      sec.gcatbar_cat = cat_gcatbar
      sec.gkbar_ikc = ikc_gkbar * ikc_gbar_dendm
      sec.gbar_cagk = cagk_gbar
      for seg in sec:
        d = h.distance(seg.x,sec=sec)
        seg.hcnwino.ghbar = gbar_h * exp(d/h_lambda)
        seg.gmax_km = km_gmax * exp(d/h_lambda)
        seg.gbar_kap = soma.gbar_kap * exp(d/h_lambda)
        seg.gbar_kdr = soma.gbar_kdr * exp(d/h_lambda)
    self.apic[1].gcalbar_cal = cal_gcalbar * calginc # middle apical dend gets more iL
    self.apic[2].cm = 2.0

    Bdend = self.Bdend
    Bdend.gcalbar_cal = cal_gcalbar * cal_gbar_bdendm
    Bdend.gcanbar_can = can_gcanbar * can_gbar_bdendm
    Bdend.gcatbar_cat = cat_gcatbar * cat_gbar_bdendm
    Bdend.gkbar_ikc = ikc_gkbar * ikc_gbar_dendm
    Bdend.gbar_cagk = cagk_gbar
    Bdend.gbar_kap = soma.gbar_kap; Bdend.gbar_kdr = soma.gbar_kdr
    Bdend.gmax_km = km_gmax

  def set_conductances (self): # insert the conductances
    for sec in self.all_sec:
      sec.insert('k_ion')
      sec.insert('na_ion')
      sec.insert('ca_ion')
      sec.insert('pas')         # passive   
      sec.insert('hcnwino') # H channel in Ih.mod
      sec.insert('nax')      # Na current
      sec.insert('kdr')      # K delayed rectifier current
      sec.insert('kap')      # K-A current
      # calcium-related channels
      sec.insert('cal') # cal_mig.mod
      sec.insert('can') # can_mig.mod
      sec.insert('cat') # cat_mig.mod
      sec.insert('ikc') # IC.mod - ca and v dependent k channel - BK
    soma = self.soma; self.soma.insert('kdmc')  # K-D current in soma only
    for sec in self.apic:
      sec.insert('km') # km.mod
      sec.insert('cagk') # cagk.mod - SK
    self.Bdend.insert('km') # km.mod
    self.Bdend.insert('cagk') # cagk.mod - SK
		
  def set_synapses(self):
    erevgaba = -80
    self.somaGABAf = Synapse(sect=self.soma,loc=0.5,tau1=0.07,tau2=9.1,e=erevgaba)
    self.somaAMPA = Synapse(sect=self.soma,loc=0.5,tau1=0.05,tau2=5.3,e=0)
    bdsyloc = 0.5 
    self.BdendAMPA = Synapse(sect=self.Bdend,loc=bdsyloc,tau1=0.05, tau2=5.3,e=0)    
    self.BdendNMDA = SynapseNMDA(sect=self.Bdend,loc=bdsyloc,tau1NMDA=tau1NMDAEE,tau2NMDA=tau2NMDAEE,r=1,e=0)
    self.Adend1GABAs = Synapse(sect=self.Adend1,loc=0.5,tau1=0.2,tau2=20,e=erevgaba)
    self.Adend2GABAs = Synapse(sect=self.Adend2,loc=0.5,tau1=0.2,tau2=20,e=erevgaba)
    self.Adend3GABAs = Synapse(sect=self.Adend3,loc=0.5,tau1=0.2,tau2=20,e=erevgaba)
    self.Adend3GABAf = Synapse(sect=self.Adend3,loc=0.5,tau1=0.07,tau2=9.1,e=erevgaba)
    self.Adend3AMPA = Synapse(sect=self.Adend3,loc=0.5,tau1=0.05,tau2=5.3,e=0)
    self.Adend3NMDA = SynapseNMDA(sect=self.Adend3,loc=0.5,tau1NMDA=tau1NMDAEE,tau2NMDA=tau2NMDAEE,r=1,e=0)
    self.Adend2AMPA = Synapse(sect=self.Adend2,loc=0.5,tau1=0.05,tau2=5.3,e=0)
    self.Adend2NMDA = SynapseNMDA(sect=self.Adend2,loc=0.5,tau1NMDA=tau1NMDAEE,tau2NMDA=tau2NMDAEE,r=1,e=0)
    self.Adend1AMPA = Synapse(sect=self.Adend1,loc=0.5,tau1=0.05,tau2=5.3,e=0)
    self.Adend1NMDA = SynapseNMDA(sect=self.Adend1,loc=0.5,tau1NMDA=tau1NMDAEE,tau2NMDA=tau2NMDAEE,r=1,e=0)
    self.Adend3mGLUR = SynapsemGLUR(sect=self.Adend3,loc=0.5)
    self.Adend3GABAB = SynapseGABAB(sect=self.Adend3,loc=0.5)
    self.Adend2mGLUR = SynapsemGLUR(sect=self.Adend2,loc=0.5)
    self.Adend2GABAB = SynapseGABAB(sect=self.Adend2,loc=0.5)
    self.Adend1mGLUR = SynapsemGLUR(sect=self.Adend1,loc=0.5)
    self.Adend1GABAB = SynapseGABAB(sect=self.Adend1,loc=0.5)

#######################################
#      some utils to avoid the h.     #
vlk = h.vlk
Vector = h.Vector
NQS = h.NQS
gg = h.gg
ge = h.ge
Random = h.Random
List = h.List
Matrix = h.Matrix
nqsdel = h.nqsdel
Graph = h.Graph
vrsz = h.vrsz
allocvecs = h.allocvecs
NetCon = h.NetCon
NetStim = h.NetStim
#######################################


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