Computer model of clonazepam`s effect in thalamic slice (Lytton 1997)

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Accession:12631
Demonstration of the effect of a minor pharmacological synaptic change at the network level. Clonazepam, a benzodiazepine, enhances inhibition but is paradoxically useful for certain types of seizures. This simulation shows how inhibition of inhibitory cells (the RE cells) produces this counter-intuitive effect.
Reference:
1 . Lytton WW (1997) Computer model of clonazepam's effect in thalamic slice. Neuroreport 8:3339-43 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Thalamus;
Cell Type(s): Thalamus geniculate nucleus (lateral) principal neuron; Thalamus reticular nucleus cell;
Channel(s): I Na,t; I T low threshold; I K; I CAN;
Gap Junctions:
Receptor(s): GabaA; Gaba;
Gene(s):
Transmitter(s): Gaba;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Bursting; Therapeutics; Epilepsy; Calcium dynamics;
Implementer(s): Lytton, William [billl at neurosim.downstate.edu];
Search NeuronDB for information about:  Thalamus geniculate nucleus (lateral) principal neuron; Thalamus reticular nucleus cell; GabaA; Gaba; I Na,t; I T low threshold; I K; I CAN; Gaba;
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lytton97b
README
AMPA.mod
calciumpump_destexhe.mod *
GABAA.mod
GABAB1.mod
GABALOW.mod
HH_traub.mod *
IAHP_destexhe.mod
ICAN_destexhe.mod
ICAN_voltdep.mod
Ih_old.mod *
IT_wang.mod
IT2_huguenard.mod
NMDA.mod
passiv.mod *
pregen.mod *
presyn.mod *
pulse.mod
rand.mod
bg.inc *
boxes.hoc
ctl.dat
ctlnew.dat
czp.dat
czpnew.dat
declist.hoc *
decvec.hoc *
default.hoc *
disp.hoc
Fig3.gif
Fig4.gif
geom.hoc
grvec.hoc
init.hoc
labels.hoc
local.hoc
mod_func.c
mosinit.hoc
network.hoc
neurrep8
nrnoc.hoc
params.hoc
presyn.inc *
queue.inc *
run.hoc
show.hoc
simctrl.hoc *
sns.inc *
snsarr.inc
snscode.hoc
snsgr.hoc
snshead.inc *
synq.inc *
xtmp
                            
// $Id: boxes.hoc,v 1.1 2002/07/27 19:16:02 hines Exp hines $

proc boxes () {}

// factor(num) finds the factors that are closest together
// NB: must be at top since declared external in template BX
func factor () { local num, srt, ii
  num = $1
  srt = int(sqrt(num))
  for (ii=srt;ii<num && num/ii!=int(num/ii);ii+=1) {}
  if (ii>num/ii) ii=num/ii // return smaller factor
  return ii
}

// template for putting up trays and decks
begintemplate BX
public mktray,mkdeck,name,boxes
public min,max,attrnum,rows,cols
external rv,gv,factor

objref boxl, boxes[3], ob, gitem
double min[1],max[1]
strdef temp_string_,name

proc init () {
  min = -1 max = -1
  boxl = new List()
}

//mktray(panattr) graph out from llist of a panattr
proc mktray () { local ci, ri, gi, m1, m2, bi
  attrnum=$2
  ob = $o1.object($2)
  cols=$4 rows=$3
  if (numarg()==6) {xs=$5 ys=$6} else {xs=100 ys=50}
  ri = 0 // count the rows
  gi = 0 // count the graphs
  boxes[0] = new VBox()
  boxes[0].intercept(1)
  name="                "
  xpanel("",1)
  xvarlabel(name)
  xpanel()
    for ri=0,rows-1 {
    boxes[2] = new HBox()
    boxl.append(boxes[2])
    bi = boxl.count-1
    boxl.object(bi).intercept(1)
    for ci=0,cols-1 {
      gitem = new Graph(0)
      gitem.view(0,-100,1000,50,0,0,xs,ys)
      ob.glist.append(gitem)
      gi = gi+1
    }
    boxl.object(bi).intercept(0)
    boxl.object(bi).map("")
  }
  boxes[0].intercept(0)
  if (strcmp(name,"")==0) boxes[0].map(ob.filename) else {
    boxes[0].map(name) }
}

proc mkdeck () { local rows, cols, ci, ri, gi, m1, m2
  ob = $o1.object($2)
  if (min==-1 || max==-1) {
    m1 = 0 m2 = ob.llist.count()-1
  } else { m1=min    m2=max }
  cnt = m2-m1+1
  cols=factor(cnt) rows=cnt/factor(cnt)
  ri = 0 // count the rows
  gi = 0 // count the graphs
  boxes[0] = new VBox()
  boxes[0].intercept(1)
  xpanel("",1)
  xbutton("Next","boxes[1].flip_to(decknum=decknum+1)")
  xbutton("Previous","boxes[1].flip_to(decknum=decknum-1)")
  xpanel()
  boxes[1] = new Deck()
  boxes[1].intercept(1)
  for ri=0,rows-1 {
    boxes[2] = new HBox()
    boxl.append(boxes[2])
    boxes[2].intercept(1)
    for ci=0,cols-1 {
      rv($2,gi+m1)
      gi = gi+1
    }
    boxes[2].intercept(0)
    boxes[2].map("")
  }
  boxes[1].intercept(0)
  boxes[1].map("")
  boxes[0].intercept(0)
  boxes[0].map("Deck")
  decknum = 0
  boxes[1].flip_to(decknum)
  if ($2!=0) {
    for ii = 0,gi-1 { 
      ob.glist.object(ii).label(0.3,0.5,ob.llist.object(ii).name)
    }
  }
}

endtemplate BX

objref boxer, boxerl
boxerl = new List()
proc mktray () { 
  if (numarg()==0) { print "mktray(attrnum,rows,cols[,xsize,ysize,label])"
    print "Create a tray for attr panel ATTRNUM to superimpose upon."
    return }
  boxer = new BX()
  boxerl.append(boxer)
  if ($1>panobjl.count-1) {
    attrlist(5,$1,"NEW","",printStep)
  }
  panobjl.object($1).super = 1
  if (numarg()==4) { boxer.name=$s4 }
  if (numarg()==6) { boxer.name=$s6 }
  if (numarg()>3 && numarg()!=4) {
    boxer.mktray(panobjl,$1,$2,$3,$4,$5)
  } else {
    boxer.mktray(panobjl,$1,$2,$3)
  }
  boxer=nil
}

proc rmtray () { local attrnum
  attrnum=$1
  if (boxerl.count<=1) boxerl.remove_all else {
    for (ii=boxerl.count-1;ii>=0;ii-=1) {
      if (boxerl.object(ii).attrnum==attrnum) boxerl.remove(ii) 
    }}
  remgrs(attrnum)
  panobj.super=0
}

proc trsz () {
  if (boxerl.count>0) for ltr (XO,boxerl) printf("%d:%d x %d\n",XO.attrnum,XO.rows,XO.cols)
}

proc mktrpanl () {
  xgetargs("Make Tray","mktray","Which","rows","cols","xsize","ysize","0,2,3,100,50")
}

lastdisp = 0
proc disptray () { local ii,jj,kk
  if (numarg()==0) {print "disptray(attrnum[,cols])" return}
  lastdisp=attrnum=$1
  ii=panobjl.object(attrnum).llist.count 
  if (numarg()==2) jj=$2 else jj=factor(ii)
  kk=panobjl.object(attrnum).glist.count
  mktray(attrnum,ii/jj,jj,100,50) 
  grall(attrnum,0,ii-1,attrnum,kk)
  for ltr(XO,panobjl.object(attrnum).glist) if(i1>=kk) { 
    XO.size(&x[0]) 
    XO.size(x[0],x[1],x[2],x[3]) }
}

proc redisptr () { 
  if (numarg()==1) lastdisp=$1
  geall(lastdisp) grall(lastdisp)
}

Lytton WW (1997) Computer model of clonazepam's effect in thalamic slice. Neuroreport 8:3339-43[PubMed]

References and models cited by this paper

References and models that cite this paper

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