Amyloid beta (IA block) effects on a model CA1 pyramidal cell (Morse et al. 2010)

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Accession:87284
The model simulations provide evidence oblique dendrites in CA1 pyramidal neurons are susceptible to hyper-excitability by amyloid beta block of the transient K+ channel, IA. See paper for details.
Reference:
1 . Morse TM, Carnevale NT, Mutalik PG, Migliore M, Shepherd GM (2010) Abnormal Excitability of Oblique Dendrites Implicated in Early Alzheimer's: A Computational Study. Front Neural Circuits [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): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I h; I K,Ca;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Active Dendrites; Detailed Neuronal Models; Pathophysiology; Aging/Alzheimer`s;
Implementer(s): Carnevale, Ted [Ted.Carnevale at Yale.edu]; Morse, Tom [Tom.Morse at Yale.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I h; I K,Ca;
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CA1_abeta
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readme.html
cacumm.mod
cagk.mod *
cal2.mod *
can2.mod *
cat.mod *
distr.mod *
h.mod
ipulse2.mod *
kadist.mod
kaprox.mod
kdrca1.mod
na3n.mod
naxn.mod *
zcaquant.mod
aBeta.hoc
add_ca.hoc
bAP_peak_vecs.hoc
c91662.ses
C91662_Link.txt
cond_report.hoc
control_boxes.hoc
distribute_currents.hoc
fig1.jpg
fig2.jpg
fig2A_c91662.hoc
fig3.jpg
fig3.ses
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fig4.ses
fig5.jpg
fig6b.jpg
figs.hoc
find_averages.hoc
fixnseg.hoc
GaspiriniEtAl2007Fig1Stimulation.ses
generate_conc_graph.hoc
gka_averager.hoc
graph_na3_kinetics.hoc
init_and_run_and_graph.hoc
leaky_distal.hoc
maxica.hoc
maxica.ses.20100525
mosinit.hoc
na3_shifter.hoc
ntc_additions.hoc
oblique_application.hoc
oblique_scaled_ka.hoc
obliques_primary_tuft.hoc
paper_fig_buttons.hoc
sectiontest.hoc
shrink_obliques.hoc
SubBranch.hoc
trigger_and_start.hoc
wait_for_go.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  }
}