Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)

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Accession:185858
"Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. ..."
Reference:
1 . Neymotin SA, McDougal RA, Bulanova AS, Zeki M, Lakatos P, Terman D, Hines ML, Lytton WW (2016) Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex Neuroscience 316:344-366 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell; Synapse; Channel/Receptor; Molecular Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic cell; Neocortex V1 L2/6 pyramidal intratelencephalic cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex layer 2-3 interneuron; Neocortex layer 5 interneuron; Neocortex layer 6a interneuron;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I CAN; I Calcium; I_AHP; I_KD; Ca pump;
Gap Junctions:
Receptor(s): mGluR1; GabaA; GabaB; AMPA; NMDA; mGluR; Glutamate; Gaba; IP3;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Ion Channel Kinetics; Oscillations; Spatio-temporal Activity Patterns; Signaling pathways; Working memory; Attractor Neural Network; Calcium dynamics; Laminar Connectivity; G-protein coupled; Rebound firing; Brain Rhythms; Dendritic Bistability; Reaction-diffusion; Beta oscillations; Persistent activity; Multiscale;
Implementer(s): Neymotin, Sam [samn at neurosim.downstate.edu]; McDougal, Robert [robert.mcdougal at yale.edu];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic cell; Neocortex V1 L2/6 pyramidal intratelencephalic cell; Neocortex V1 interneuron basket PV cell; mGluR1; GabaA; GabaB; AMPA; NMDA; mGluR; Glutamate; Gaba; IP3; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I CAN; I Calcium; I_AHP; I_KD; Ca pump; Gaba; Glutamate;
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CaHDemo
readme.html
cagk.mod
cal.mod *
calts.mod *
can.mod *
cat.mod *
gabab.mod
IC.mod *
icalts.mod *
Ih.mod
ihlts.mod *
IKM.mod *
kap.mod
kcalts.mod *
kdmc.mod
kdr.mod
kdrbwb.mod
km.mod *
mglur.mod *
misc.mod
MyExp2SynBB.mod *
MyExp2SynNMDABB.mod
nafbwb.mod
nax.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 *
onepyr.cfg
onepyr.py
pyinit.py *
python.hoc *
pywrap.hoc *
screenshot.png
screenshot1.png
simctrl.hoc *
simdat.py
syncode.hoc *
xgetargs.hoc *
                            
// $Id: labels.hoc,v 1.104 2012/04/12 01:44:03 samn Exp $

print "Loading labels.hoc..."

{load_file("declist.hoc")}
// keep track of version number for future changes
// eg if (label_hoc_vers>88) rcsopen("labels.hoc",88) // go back to 88
labels_hoc_vers=find_num("$Id: labels.hoc,v 1.104 2012/04/12 01:44:03 samn Exp $","1\\."," ")
objref NCv,CODEv,DELv
objref PRIDv,POIDv,PRv,POv,DISTv,WT0v,WT1v // mo(1) will assign these
{declare("ce",nil,"CTYP",new List(),"CPLA",new List(),"TPA",new List(),"nm",new List())}
{declare("STYP",new List(),"ncells",0,"ZTYP",new List(),"INCOL",new List())}
{declare("DEND",0,"SOMA",1,"AXON",2)} // compartment codes - only 3 for now

scrsz=50*1e3
double scr[scrsz]

//* utility functions
// plmin(val,var)
func plmin() { return $1 + $2*(2*u_rand() - 1) } 

//* cell types: 
// iex(), returns numeric index associated with a string or string object
func iex () { 
  if (argtype(1)==2) sprint(tstr,"x=%s",$s1) else sprint(tstr,"x=%s",$o1.s)
  execute(tstr) return x 
}
// ice(), returns whether cell is an inhib cell based on its name starting with I
func ice () { local x
  if (argtype(1)==2) return strm($s1,"^I")
  if (argtype(1)==0) x=$1 else if (argtype(1)==1) x=$o1.type 
  return strm(CTYP.o(x).s,"^I")
}
//* GetLyr - return layer of type
func GetLyr () { local x localobj st
  st=new String()
  if (argtype(1)==2) st.s=$s1 else if (argtype(1)==0) st.s=CTYP.o($1).s else {
    st.s=CTYP.o($o1.type).s }
  sscanf(st.s,"%*1s%d",&x)
  return x
}

proc printtype () { local i
  for (i=1;argtype(i)==0;i+=1) if ($i!=-1) printf("%s(%d) ",CTYP.o($i).s,$i)
  if (argtype(i)==2) printf("%s",$si) else print ""
}
proc celltype () { localobj st
  st=new String("\n")
  if (argtype(2)==2) st.s=$s2
  if (argtype(1)==0) printtype(ce.o($1).type,st.s) else printtype($o1.type,st.s) 
}

obfunc names2indices () { local x localobj lo,xo,st
  lo=new List() st=new String()
  split($s1,lo)
  for ltr(xo,lo,&x) { sprint(st.s,"%s=%d",xo.s,x) execute(st.s) }
  return lo
}

// at some point may want to divide up this list into cell type -- eg RS,IB and location
CTYP=names2indices("NU,SM,DP,SU,IN,TC,IRE,ITH,E6,I6,I6C,I6L,E5B,E5R,I5,I5L,E4,I4,I4L,E2,E2B,I2,I2Q,I2C,I2L,RS,IB,LTS,FS,ECA1,ICA1,ICA1L,EDG,IDG,IDGL,ECA3,ICA3,ICA3L,E3,I3,I3L,ES,IS,ISL,EM,IM,IML,EV,IV,IVL")
CTYPi=CTYP.count  // number of cell types
EXCIT=-1  // don't know how to fit these in best
INHIB=-2

// 1 cmp nrn, 2 cmp nrn, multi cmp nrn, intfire1, INTF, invlfire, nstim
for scase2(XO,"1-CMP","CMP1","2-CMP","CMP2","MULTI-CMP","MC","IntFire1","IF1","INTF","IF",\
          "INVLF","IFV","NStim","STM") { CPLA.append(XO)
  sprint(tstr,"%s=%d",XO.t,i1) execute(tstr) }
CPLAi=CPLA.count // count of cell templates

for scase2(XO,"REAL","RL","ARTC","AC","SOMA","SO","DEND","DN") {TPA.append(XO)}
TPAi=TPA.count

proc ae () { localobj xo
  STYP.remove_all
  for scase2(xo,"AMPA","AM","NMDA","NM","GABAA","GA","GABAB","GB",\
             "AMPA2","AM2","NMDA2","NM2","GABAA2","GA2","GABAB2","GB2",\
             "IClamp","IC","AMPA/NMDA","EX","GABAA/GABAB2","IX",\
             "Exp2Syn","E2Sy"){
    STYP.append(new String2(xo.t,xo.s)) // switch them around here
    sprint(tstr,"%s=%d",xo.t,i1)
    execute(tstr)
  }
  STYPi=STYP.count  // number of cell types
}
ae()

for scase(XO,"DG","CA3","CA1","SUB","PSUB","MEC","LEC") {
  sprint(tstr,"%s=%d",XO.s,i1) execute(tstr) ZTYP.append(new String(XO.s))
}

for scase2(XO,"RIGHT","RIT","INCOL","INC","LEFT","LFT") { INCOL.append(new String(XO.s))
  sprint(tstr,"%s=%d",XO.t,i1) execute(tstr) }
INCOLi=INCOL.count

//* IsLTS - return if type is LTS
func IsLTS () {
  return $1 == I2L || $1 == I4L || $1 == I5L || $1 == I6L || $1 == ISL || $1 == IML || $1 == IVL
}
//* IsBurst - return if type is intrinsically bursting
func IsBurst () {
  return $1 == E2B || $1 == E5B
}
//* IsFRB - return true if type is fast regular bursting
func IsFRB () {
  return $1 == E2B
}
//* IsRS - return true if type is regular spiking E cell
func IsRS () {
  return $1 == E2 || $1 == E4 || $1 == E5R || $1 == E6 || $1 == ES || $1 == EM || $1 == EV
}
//* IsFS - return true if type is fast spiking interneuron
func IsFS () {
  return $1==I2 || $1==I4 || $1==I5 || $1==I6 || $1==ICA3 || $1==IDG || $1==ICA1 || $1==IS || $1==IM || $1==IV
}
//* IsTHAL - return true if type is from thalamus
func IsTHAL () {
  return $1 == TC || $1 == IRE
}

func isartcell () { return sfunc.is_point_process($o1) }