Spatial constrains of GABAergic rheobase shift (Lombardi et al., accepted)

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In this models we investigated how the threshold eGABA, at which GABAergic inhibition switches to excitation, depends on the spatiotemporal constrains in a ball-and-stick neurons and a neurons with a topology derived from an reconstructed neuron.
1 . Lombardi A, Luhmann HJ, Kilb W (accepted) Modelling the spatial and temporal constrains of the GABAergic influence on neuronal excitability PLoS Computational Biology
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal GLU cell;
Gap Junctions:
Receptor(s): AMPA; GabaA;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Development; Action Potentials;
Implementer(s): Kilb, Werner [wkilb at];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal GLU cell; GabaA; AMPA; Gaba; Glutamate;
GPAS = 1.28e-005

proc celldef() {

create soma, dend

proc topol() { local i
  connect dend(0), soma(1)

objref all, with_AP, wo_AP
proc subsets() { local i
  objref all, with_HH, wo_HH
  all = new SectionList()
    soma all.append()
    dend all.append()

  with_AP = new SectionList()
    soma with_AP.append()

  wo_AP = new SectionList()
    dend wo_AP.append()

proc geom() {
  forsec all {  }
  soma {  L = 46.6  diam = 46.6  nseg = 11}
  dend {  L = 1000  diam = 1  nseg = 301}

proc biophys() {
  forsec all {
    cm = 2
    Ra = 35.4
  forsec with_AP {
     insert ndrfAP
     insert pas 
       g_pas = GPAS
       e_pas = -50.5
  forsec wo_AP {
      insert pas
        g_pas = GPAS
        e_pas = -50.5
access soma


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