Modelling reduced excitability in aged CA1 neurons as a Ca-dependent process (Markaki et al. 2005)

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Accession:119266
"We use a multi-compartmental model of a CA1 pyramidal cell to study changes in hippocampal excitability that result from aging-induced alterations in calcium-dependent membrane mechanisms. The model incorporates N- and L-type calcium channels which are respectively coupled to fast and slow afterhyperpolarization potassium channels. Model parameters are calibrated using physiological data. Computer simulations reproduce the decreased excitability of aged CA1 cells, which results from increased internal calcium accumulation, subsequently larger postburst slow afterhyperpolarization, and enhanced spike frequency adaptation. We find that aging-induced alterations in CA1 excitability can be modelled with simple coupling mechanisms that selectively link specific types of calcium channels to specific calcium-dependent potassium channels."
Reference:
1 . Markaki M, Orphanoudakis S, Poirazi P (2005) Modelling reduced excitability in aged CA1 neurons as a calcium-dependent process Neurocomputing 65-66:305-314
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: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I N; I A; I K; I M; I K,Ca; I R;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Aging/Alzheimer`s;
Implementer(s):
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; I Na,p; I Na,t; I L high threshold; I N; I A; I K; I M; I K,Ca; I R;
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CA1_Aged
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 *
mod_func.c *
newshiftsyn *
newshiftsyn.c *
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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