CA1 pyramidal neuron: functional significance of axonal Kv7 channels (Shah et al. 2008)

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The model used in this paper confirmed the experimental findings suggesting that axonal Kv7 channels are critically and uniquely required for determining the inherent spontaneous firing of hippocampal CA1 pyramids, independently of alterations in synaptic activity. The model predicts that the axonal Kv7 density could be 3-5 times that at the soma.
1 . Shah MM, Migliore M, Valencia I, Cooper EC, Brown DA (2008) Functional significance of axonal Kv7 channels in hippocampal pyramidal neurons. Proc Natl Acad Sci U S A 105(22):7869-7874 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,t; I T low threshold; I A; I K; I M; I Calcium;
Gap Junctions:
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Detailed Neuronal Models; Axonal Action Potentials; Action Potentials;
Implementer(s): Migliore, Michele [Michele.Migliore at];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; I Na,t; I T low threshold; I A; I K; I M; I Calcium;
cacumm.mod *
cat.mod *
h.mod *
kadist.mod *
KahpM95.mod *
kaprox.mod *
kdrca1.mod *
km.mod *
na3n.mod *
naxn.mod *
fixnseg.hoc *
geo9068802.hoc *
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  }