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 *
                            
// For each band of gaba background synapses, this function makes a file with the
// stimulation train and shifts the activation time (by temporal_offset)  
// written by Yiota Poirazi, July 2001, poirazi@LNC.usc.edu

double iary_bg[1000]
objref vary_bg[1000], s_file, stimtmp, rpid
stimtmp = new Vector()
strdef shiftsyn_filename, syscmd, estr

proc gaba_shift() { local synapses, temporal_offset, hertz, gmax_default, PID, lo, hi

synapses = $1        // number of synapses in the band
tstop = $2           // stimulation end time
dt = $3   
hertz = $4           // stimulation train frequency
synch = $5           // synchronous or a synchronous stimulation of synapses
perio = $6           // periodic or not periodic stimulation
PID = $7
PID = abs(PID)       // only positive random seeds used for spike train generation 
temporal_offset = $8 // shift stimulation time by temporal_offset

// Make the desired activation pattern file and
// Set GABA pointers to activation pattern

   sprint(shiftsyn_filename,"gaba_shiftsyn-%d-%.2f-%.2f-%.2f-%.2f-%.2f-%d-%.2f",\
         synapses,tstop,dt,hertz,synch,perio,PID,temporal_offset)   // filename
   
   sprint(syscmd,"newshiftsyn gaba_shiftsyn %d %g %g %g %g %g %d %g",\
         synapses,tstop,dt,hertz,synch,perio,PID,temporal_offset)    // use newshiftsyn to make
								     // stimulation train	
   system(syscmd)  // Same as typing syscmd in DOS, execute above command
   print  syscmd

  s_file = new File()
  s_file.ropen(shiftsyn_filename) // open the stimulation train file

  stimtmp.scanf(s_file)           // read temporal stimulation pattern in a 1-d vector
  s_file.close()

  items = int(tstop/dt)           // number of stimuli (firing patterns) for each synapse

  for i=0,synapses-1 {
  //  printf(" -- synapse %d\n", i)

    vary_bg[i] = new Vector(items)  // for each synapse, save firing pattern in this vector

  // Put the firing patterns from stimtmp (1-d vector) to a 2-d vector for each synapse i
 
    for j=0,items-1 {   
        vary_bg[i].x[j]=stimtmp.x[i + j*synapses] 
      
     }
  }

//  print "setpointer to each synapse"

    for s=0, synapses-1 {
        sprint(estr,"vary_bg[%d].play(&iary_bg[%d])", s,s)
        execute1(estr)
//        print estr

      	sprint(estr,"setpointer gabaa_bg[%d].pre, iary_bg[%d]", s,s)
        execute1(estr)
//        print estr

        sprint(estr,"setpointer gabab_bg[%d].pre, iary_bg[%d]", s,s)
        execute1(estr)
//        print estr
       
    }

sprint(econ.syscmd,  "rm -f %s", shiftsyn_filename) // remove firing pattern file
system(econ.syscmd)

sprint(econ.syscmd,  "rm -f ERROR*")                // if an error file is generated, remove it as well
system(econ.syscmd)                              // that don't affect the firing patterns generated
 						 // if errors do happen, NEURON crashes	
}






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