Layer V PFC pyramidal neuron used to study persistent activity (Sidiropoulou & Poirazi 2012)

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Accession:144089
"... Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. ... Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression. "
Reference:
1 . Sidiropoulou K, Poirazi P (2012) Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons. PLoS Comput Biol 8:e1002489 [PubMed]
Citations  Citation Browser
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): Neocortex V1 L6 pyramidal corticothalamic GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I A; I K; I K,Ca; I CAN;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA; IP3;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Detailed Neuronal Models;
Implementer(s): Sidiropoulou, Kyriaki [sidirop at imbb.forth.gr];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic GLU cell; GabaA; GabaB; AMPA; NMDA; IP3; I Na,p; I Na,t; I L high threshold; I A; I K; I K,Ca; I CAN; Gaba; Glutamate;
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PFCcell
lib
basic-graphics.hoc *
choose-secs.hoc
current-balance.hoc
cut-sections.hoc *
distance.hoc
ken.h *
map-segments-to-3d.hoc *
mod_func.c *
newshiftsyn *
newshiftsyn.c *
num-rec.h *
salloc.hoc
vector-distance.hoc *
verbose-system.hoc *
                            
// For each section location, define x,y,z coordinates so it can be
// displayed in 3-D

proc endpt() {
  P=(n3d()-1)*$1

  x_d3($1)=x3d(P)
  y_d3($1)=y3d(P)
  z_d3($1)=z3d(P)

}
proc fracpt() { local posn, A
  A=$1
  posn=$2
  x_d3(posn)=x3d(i-1) + (x3d(i) - x3d(i-1))*A
  y_d3(posn)=y3d(i-1) + (y3d(i) - y3d(i-1))*A
  z_d3(posn)=z3d(i-1) + (z3d(i) - z3d(i-1))*A

}
proc map_segments_to_3d() {

    forall {
    
    insert d3
    i=0
    endpt(0)

    for (x) if (x > 0 && x < 1) {

      while (arc3d(i)/L < x) {
        i += 1
      }
      D=arc3d(i) - arc3d(i-1)
      if (D <= 0) {
      printf("\t\t * %s had a D < 0\n", secname())
      }
      alpha = (x*L - arc3d(i-1))/D
      fracpt(alpha,x)

    }
    endpt(1)

  }
}