ModelDB is moving. Check out our new site at https://modeldb.science. The corresponding page is https://modeldb.science/147141.

Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)

 Download zip file 
Help downloading and running models
Accession:147141
Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered.
Reference:
1 . Rowan MS, Neymotin SA (2013) Synaptic Scaling Balances Learning in a Spiking Model of Neocortex Adaptive and Natural Computing Algorithms, Tomassini M, Antonioni A, Daolio F, Buesser P, ed. pp.20
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Abstract integrate-and-fire adaptive exponential (AdEx) neuron;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Synaptic Plasticity; Long-term Synaptic Plasticity; Learning; STDP; Homeostasis;
Implementer(s): Lytton, William [bill.lytton at downstate.edu]; Neymotin, Sam [Samuel.Neymotin at nki.rfmh.org]; Rowan, Mark [m.s.rowan at cs.bham.ac.uk];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; GabaA; AMPA; NMDA; Gaba; Glutamate;
/
stdpscalingpaper
batchscripts
mod
README
alz.hoc
autotune.hoc *
basestdp.hoc *
batch.hoc *
batch2.hoc *
batchcommon
checkirreg.hoc *
clusterrun.sh
col.dot *
col.hoc *
comppowspec.hoc *
condisconcellfig.hoc *
condisconpowfig.hoc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
e2hubsdisconpow.hoc *
e2incconpow.hoc *
filtutils.hoc *
geom.hoc *
graphplug.hoc *
grvec.hoc *
init.hoc *
labels.hoc *
load.hoc *
local.hoc *
makepopspikenq.hoc *
matfftpowplug.hoc *
matpmtmplug.hoc *
matpmtmsubpopplug.hoc *
matspecplug.hoc *
network.hoc *
nload.hoc *
nqpplug.hoc *
nqs.hoc *
nqsnet.hoc *
nrnoc.hoc *
params.hoc
plot.py
plotbatch.sh
plotbatchcluster.sh
powchgtest.hoc *
python.hoc *
pywrap.hoc *
redE2.hoc *
run.hoc
runsim.sh
setup.hoc *
shufmua.hoc *
sim.hoc
simctrl.hoc *
spkts.hoc *
stats.hoc *
stdpscaling.hoc
syncode.hoc *
vsampenplug.hoc *
writedata.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) }


Loading data, please wait...