CA3 pyramidal neuron (Safiulina et al. 2010)

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Accession:126814
In this review some of the recent work carried out in our laboratory concerning the functional role of GABAergic signalling at immature mossy fibres (MF)-CA3 principal cell synapses has been highlighted. To compare the relative strength of CA3 pyramidal cell output in relation to their MF glutamatergic or GABAergic inputs in postnatal development, a realistic model was constructed taking into account the different biophysical properties of these synapses.
Reference:
1 . Safiulina VF, Caiati MD, Sivakumaran S, Bisson G, Migliore M, Cherubini E (2010) Control of GABA release at mossy fiber-CA3 connections in the developing hippocampus Front Synaptic Neurosci 2:1 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA3 pyramidal cell;
Channel(s): I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I M; I h; I Calcium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Dendritic Action Potentials; Bursting; Temporal Pattern Generation; Active Dendrites; Detailed Neuronal Models; Action Potentials; Synaptic Integration; Spike Frequency Adaptation;
Implementer(s): Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  Hippocampus CA3 pyramidal cell; I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I M; I h; I Calcium; Gaba; Glutamate;
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develop
readme.html
cacumm.mod *
cagk.mod *
cal2.mod *
can2.mod *
cat.mod *
h.mod *
KahpM95.mod *
kaprox.mod *
kdrca1.mod *
km.mod *
na3n.mod *
develop.hoc
develop.ses
ec-cell1zr-loop.hoc
fixnseg.hoc *
gabaAt20.jpg
gabaAt40.jpg
geo-cell1zr.hoc *
gluAt20.jpg
gluAt40.jpg
mosinit.hoc
                            
/* Sets nseg in each section to an odd value
   so that its segments are no longer than 
     d_lambda x the AC length constant
   at frequency freq in that section.

   Be sure to specify your own Ra and cm before calling geom_nseg()

   To understand why this works, 
   and the advantages of using an odd value for nseg,
   see  Hines, M.L. and Carnevale, N.T.
        NEURON: a tool for neuroscientists.
        The Neuroscientist 7:123-135, 2001.
*/

// these are reasonable values for most models
freq = 100      // Hz, frequency at which AC length constant will be computed
d_lambda = 0.1

func lambda_f() { local i, x1, x2, d1, d2, lam
        if (n3d() < 2) {
                return 1e5*sqrt(diam/(4*PI*$1*Ra*cm))
        }
// above was too inaccurate with large variation in 3d diameter
// so now we use all 3-d points to get a better approximate lambda
        x1 = arc3d(0)
        d1 = diam3d(0)
        lam = 0
        for i=1, n3d()-1 {
                x2 = arc3d(i)
                d2 = diam3d(i)
                lam += (x2 - x1)/sqrt(d1 + d2)
                x1 = x2   d1 = d2
        }
        //  length of the section in units of lambda
        lam *= sqrt(2) * 1e-5*sqrt(4*PI*$1*Ra*cm)

        return L/lam
}

proc geom_nseg() {
  soma area(0.5) // make sure diam reflects 3d points
  forall { nseg = int((L/(d_lambda*lambda_f(freq))+0.9)/2)*2 + 1  }
}