Spine fusion and branching effects synaptic response (Rusakov et al 1996, 1997)

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Accession:18502
This compartmental model of a hippocampal granule cell has spinous synapses placed on the second-order dendrites. Changes in shape and connectivity of the spines usually does not effect the synaptic response of the cell unless active conductances are incorporated into the spine membrane (e.g. voltage-dependent Ca2+ channels). With active conductances, spines can generate spike-like events. We showed that changes like fusion and branching, or in fact any increase in the equivalent spine neck resistance, could trigger a dramatic increase in the spine's influence on the dendritic shaft potential.
References:
1 . Rusakov DA, Richter-Levin G, Stewart MG, Bliss TV (1997) Reduction in spine density associated with long-term potentiation in the dentate gyrus suggests a spine fusion-and-branching model of potentiation. Hippocampus 7:489-500 [PubMed]
2 . Rusakov DA, Stewart MG, Korogod SM (1996) Branching of active dendritic spines as a mechanism for controlling synaptic efficacy. Neuroscience 75:315-23 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s): Dentate gyrus granule cell;
Channel(s): I Na,t; I K; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Synaptic Plasticity; Long-term Synaptic Plasticity;
Implementer(s): Rusakov, DA [D.Rusakov at ion.ucl.ac.uk];
Search NeuronDB for information about:  Dentate gyrus granule cell; AMPA; NMDA; I Na,t; I K; I K,Ca; I Sodium; I Calcium; I Potassium;
/* NEURON hoc program. Random 
topography of spines. 
Control situation. */

load_file("nrngui.hoc")

  /* creating soma */
create soma[3]	
access soma[0]
  nseg=3
  diam=12
  L=3
  insert hh
access soma[1]
  nseg=3
  diam=15
  L=9
  insert hh
access soma[2]
  nseg=3
  diam=12
  L=3
  insert hh
for i=0,1 soma[i] {
   connect soma[i+1](0), soma[i](1)
}
   /* creating dendrites */

create dend0
access dend0
   nseg=10
   diam=2
   L=5
   insert pas
create dend1[2]
for i=0,1 dend1[i] {
   nseg=5
   diam=1
   L=40
   insert pas
}
create dend2[4]
for i=0,3 dend2[i] {
   nseg=120
   diam=0.85
   L=60
   insert pas
}
create dend3[8]
for i=0,7 dend3[i] {
   nseg=5
   diam=0.8
   L=40
   insert pas
}
/* create dend4[16]
for i=0,15 dend4[i] {
   nseg=3
   diam=0.65
   L=20
   insert pas 
} */
    /* creating spine stems */
objectvar rr[60]  //  random stem diameters
create spins[60]
for i=0,59 spins[i] {
   rr[i] = new Random()   
   rr[i].normal(0.18,0.0121)
   x=(rr.repick())
   nseg=10
//   diam=0.1
   if (x<0.02) x=abs(x)+0.02
   diam=x
   L=1
   insert pas
 }
  /* creating spine heads and AZ*/
coord_cadifus()
create spinh[60]
create spina[60]
for i=0, 59 spinh[i] {
   nseg=2
   diam=1
   L=0.7
/* regenerative Ca2+ mechanisms 
are adjusted */
   insert cachan
   insert cagk
   insert cadifpmp
   pcabar_cachan=0.002
   gkbar_cagk=0.1
   ek=-95
   taufactor_cachan=0.5
   cai=1e-04
   cao=1.
   pump0_cadifpmp=1e-13 /* 3e-14 is 
default */
 }
for i=0, 59 spina[i] {
   nseg=1
   diam=1
   L=0.1  
   insert pas
}

  /* connecting spine heads and stems */
for i=0, 59 {
   connect spinh[i](0), spins[i](1)
   connect spina[i](0), spinh[i](1)
}
   /* connecting dendrites */
connect dend0(0), soma[2](1)
for i=0,1 {
   connect dend1[i](0), dend0(1)
}
for i=0,3 {
    j=int(i/2+.001)
    connect dend2[i](0), dend1[j](1)
}
for i=0,7 {
    j=int(i/2+.001)
    connect dend3[i](0), dend2[j](1)
}
/* for i=0,15 {
    j=int(i/2+.001)
    connect dend4[i](0), dend3[j](1)
} */
      /* connecting spines */

objectvar r[60]
for i=0,59 spins[i] {
   r[i] = new Random()
   r[i].uniform(30,40)
    j=int(i/15+0.001)  /* j=0..3, 
parent branch No for each 15 spines */
//k=int(i-((j+0.00001)*15)+0.001)  //k=0..14
//l=int(k/3+0.001)  //l=0..4, No of spine clusters per branch
     x=(r.repick())/60.
     connect spins[i](0), dend2[j](x)
}
/*  putting one AMPA-type 
    (alpha-function) 
    and one NMDA-type synapse 
    at each spine AZ */
syncur=0.00025
objectvar asyn[80]
objectvar nsyn[80]
for i=0,59 spina[i] {
   asyn[i]=new AlphaSynapse(1)
   asyn[i].tau=0.25
   asyn[i].onset=15
   asyn[i].gmax=syncur
   asyn[i].e=0
   nsyn[i]=new NMDAsyn(1)
   nsyn[i].tau1=80
   nsyn[i].tau2=0.67
   nsyn[i].onset=15
   nsyn[i].gmax=0.4*syncur
   nsyn[i].e=0
}
/* putting 20 AMPA+NMDA-type 
synapses in the middle of 2nd 
somatic compartment in order 
to achieve a continious 
depolirisation level */
access soma[1]
for i=60,79 {
   asyn[i]=new AlphaSynapse(0.5)
   asyn[i].onset=2*(i-59)-1
   asyn[i].tau=0.25
   asyn[i].gmax=0.0004
   asyn[i].e=0
   nsyn[i]=new NMDAsyn(0.5)
   nsyn[i].tau1=80
   nsyn[i].tau2=0.67
   nsyn[i].onset=2*(i-59)-1
   nsyn[i].gmax=0.0004*0.4
   nsyn[i].e=0
}
forall {Ra=100}
forall {celcius=30}
tstop=50

// xopen("$(NEURONHOME)/lib/hoc/noload.hoc")
// xopen("$(NEURONHOME)/examples/ne-11.session")
// load_template("Inserter")
// load_template("PointProcessManager")
// load_proc("nrnmainmenu")
// nrnmainmenu()

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