CA1 pyramidal neuron: synaptically-induced bAP predicts synapse location (Sterratt et al. 2012)

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Accession:144490
This is an adaptation of Poirazi et al.'s (2003) CA1 model that is used to measure BAP-induced voltage and calcium signals in spines after simulated Schaffer collateral synapse stimulation. In the model, the peak calcium concentration is highly correlated with soma-synapse distance under a number of physiologically-realistic suprathreshold stimulation regimes and for a range of dendritic morphologies. There are also simulations demonstrating that peak calcium can be used to set up a synaptic democracy in a homeostatic manner, whereby synapses regulate their synaptic strength on the basis of the difference between peak calcium and a uniform target value.
Reference:
1 . Sterratt DC, Groen MR, Meredith RM, van Ooyen A (2012) Spine calcium transients induced by synaptically-evoked action potentials can predict synapse location and establish synaptic democracy. PLoS Comput Biol 8:e1002545 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I Mixed; I R; I_AHP;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Synaptic Plasticity;
Implementer(s): Sterratt, David ; Groen, Martine R [martine.groen at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; AMPA; NMDA; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I Mixed; I R; I_AHP;
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bpap
CA1_multi
lib
basic_graphics.hoc *
basic-graphics.hoc *
choose-secs.hoc *
current-balance.hoc *
cut-sections.hoc *
deduce-ratio.hoc *
find-gmax.hoc *
GABA_shiftsyn.hoc *
GABA_shiftsyn_bg.hoc *
ken.h *
map-segments-to-3d.hoc *
maxmin.hoc *
newshiftsyn.exe *
num-rec.h *
salloc.hoc *
shiftsyn-init_bg.hoc *
shiftsyn-initA.hoc *
spikecount.hoc *
tune-epsps.hoc *
vector-distance.hoc *
verbose-system.hoc *
                            
// This function is used to calculate the maximum and minimum values in a set
// written by Terrence Brannon, last modified by Yiota Poirazi, July 2001, poirazi@LNC.usc.edu

strdef maxmin_str
proc maxmin () {
  maxmin_max=-9e99
  maxmin_min= 9e99
  maxmin_samples=0
  forall {
    if (ismembrane($s1)) {
      sprint(maxmin_str, "maxmin_val=%s", $s2)
      execute1(maxmin_str)
      if (maxmin_val > maxmin_max) {
        maxmin_max=maxmin_val
      }
      if (maxmin_val < maxmin_min) {
        maxmin_min=maxmin_val
      }

     maxmin_samples=maxmin_samples+1
    }
  }

//  print "samples ", maxmin_samples
//  print "min:    ", maxmin_min
//  print "max:    ", maxmin_max


}

proc maxmin_intrinsic () {
  maxmin_max=-9e99
  maxmin_min= 9e99
  maxmin_samples=0
  forall {
      sprint(maxmin_str, "maxmin_val=%s", $s1)
      execute1(maxmin_str)
      if (maxmin_val > maxmin_max) {
        maxmin_max=maxmin_val
      }
      if (maxmin_val < maxmin_min) {
        maxmin_min=maxmin_val
      }
     maxmin_samples=maxmin_samples+1
  }

//  print "samples ", maxmin_samples
//  print "min:    ", maxmin_min
//  print "max:    ", maxmin_max



}
proc maxmin_point_process () { local pps, ppe
  maxmin_max=-9e99
  maxmin_min= 9e99
  maxmin_samples=0

  pps=$3
  ppe=$4

  for i=pps,ppe {
      sprint(maxmin_str, "maxmin_val=%s[%d].%s", $s1, i, $s2)
      execute1(maxmin_str)
      if (maxmin_val > maxmin_max) {
        maxmin_max=maxmin_val
      }
      if (maxmin_val < maxmin_min) {
        maxmin_min=maxmin_val
      }
     maxmin_samples=maxmin_samples+1
  }

//  print "Maxmin for ", $s1, "[ ].", $s2
//  print "samples ", maxmin_samples
//  print "min:    ", maxmin_min
//  print "max:    ", maxmin_max
}

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