CA3 pyramidal neurons: Kv1.2 mediates modulation of cortical inputs (Hyun et al., 2015)

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Accession:184139
This model simulates the contribution of dendritic Na+ and D-type K+ channels to EPSPs at three different locations of apical dendrites, which mimicking innervation sites of mossy fibers (MF), recurrent fibers (AC), and perforant pathway (PP).
Reference:
1 . Hyun JH, Eom K, Lee KH, Bae JY, Bae YC, Kim MH, Kim S, Ho WK, Lee SH (2015) Kv1.2 mediates heterosynaptic modulation of direct cortical synaptic inputs in CA3 pyramidal cells. J Physiol 593:3617-43 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Dendrite;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA3 pyramidal cell;
Channel(s): I A; I Sodium; I_KD;
Gap Junctions:
Receptor(s):
Gene(s): Kv1.2 KCNA2;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials;
Implementer(s):
Search NeuronDB for information about:  Hippocampus CA3 pyramidal cell; I A; I Sodium; I_KD;
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HyunEtAl2015
ReadMe.html
Exp2GluSyn.mod
KaProx.mod
KdBG40.mod
Kdr.mod
KhdM01.mod
Na.mod
E807.hoc
Fig7Bb_(IK_conditioned).hoc
Fig7Bb_(IK_control).hoc
Fig7Bc(Gin).hoc
Fig7C_(AC-EPSP).hoc
Fig7C_(MF-EPSP).hoc
Fig7C_(PP-EPSP).hoc
Fig7D_(AC-EPSP).hoc
Fig7D_(MF-EPSP).hoc
Fig7D_(PP-EPSP).hoc
Fig7E_(control).hoc
Fig7E_(lowGkd).hoc
Fig7E_(lowGkdlowGna).hoc
fixnseg.hoc *
L22.hoc
mosinit.hoc
screenshot.png
                            
/* 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  }
}


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