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]
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 GLU 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 GLU 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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objref maxica_graph[8]

objectvar save_window_, rvp_
objectvar scene_vector_[24]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-0.025,-4.65661e-10)
scene_vector_[11] = save_window_
{save_window_.view(-10, -0.025, 850, 0.025, 439, 25, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("ica")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 1, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("ica")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 1, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("ica")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("ica")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 1, 0.8, 0.9)
maxica_graph[0]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-8.73115e-11,0.003)
scene_vector_[13] = save_window_
{save_window_.view(-10, -8.73115e-11, 850, 0.003, 439, 289, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("cai")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("cai")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("cai")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("cai")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.8, 0.9)
maxica_graph[1]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-5.82077e-11,0.003)
scene_vector_[16] = save_window_
{save_window_.view(-10, -5.82077e-11, 850, 0.003, 439, 553, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("cmax_caquant")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.66262, 0.947923)
objectvar rvp_
rvp_ = new RangeVarPlot("cmax_caquant")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.66262, 0.938339)
objectvar rvp_
rvp_ = new RangeVarPlot("cmax_caquant")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.681789, 0.938339)
objectvar rvp_
rvp_ = new RangeVarPlot("cmax_caquant")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.672204, 0.933546)
maxica_graph[2]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-0.02,2.32831e-10)
scene_vector_[12] = save_window_
{save_window_.view(-10, -0.02, 850, 0.02, 766, 25, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("imax_caquant")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.611502, 0.559744)
objectvar rvp_
rvp_ = new RangeVarPlot("imax_caquant")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.611502, 0.516613)
objectvar rvp_
rvp_ = new RangeVarPlot("imax_caquant")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.598722, 0.478275)
objectvar rvp_
rvp_ = new RangeVarPlot("imax_caquant")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.582748, 0.435144)
maxica_graph[3]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-1.19209e-07,6)
scene_vector_[14] = save_window_
{save_window_.view(-10, -1.19209e-07, 850, 6, 766, 289, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("hwi_caquant")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.263259, 0.967093)
objectvar rvp_
rvp_ = new RangeVarPlot("hwi_caquant")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.263259, 0.9623)
objectvar rvp_
rvp_ = new RangeVarPlot("hwi_caquant")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.269649, 0.967093)
objectvar rvp_
rvp_ = new RangeVarPlot("hwi_caquant")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.269649, 0.976677)
maxica_graph[4]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,0,8)
scene_vector_[17] = save_window_
{save_window_.view(-10, 0, 850, 8, 766, 553, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("svr_caquant")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.64345, 0.588498)
objectvar rvp_
rvp_ = new RangeVarPlot("svr_caquant")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.643451, 0.583706)
objectvar rvp_
rvp_ = new RangeVarPlot("svr_caquant")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 2, 0.64345, 0.578914)
objectvar rvp_
rvp_ = new RangeVarPlot("svr_caquant")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.637061, 0.569329)
maxica_graph[5]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-9.31323e-10,0.06)
scene_vector_[15] = save_window_
{save_window_.view(-10, -9.31323e-10, 850, 0.06, 1093, 289, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("qapprox_caquant")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.464537, 0.914377)
objectvar rvp_
rvp_ = new RangeVarPlot("qapprox_caquant")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.461342, 0.904792)
objectvar rvp_
rvp_ = new RangeVarPlot("qapprox_caquant")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.458147, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("qapprox_caquant")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.458147, 0.885623)
maxica_graph[6]=save_window_
}
{
save_window_ = new Graph(0)
save_window_.size(-10,840,-8.73115e-11,0.003)
scene_vector_[18] = save_window_
{save_window_.view(-10, -8.73115e-11, 850, 0.003, 1093, 553, 300.48, 200.32)}
flush_list.append(save_window_)
save_window_.save_name("flush_list.")
objectvar rvp_
rvp_ = new RangeVarPlot("cmaxp_caquant")
soma rvp_.begin(1)
apic[42] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 2, 3, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("cmaxp_caquant")
soma rvp_.begin(1)
apic[53] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 3, 2, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("cmaxp_caquant")
soma rvp_.begin(1)
apic[67] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 4, 1, 0.8, 0.9)
objectvar rvp_
rvp_ = new RangeVarPlot("cmaxp_caquant")
soma rvp_.begin(1)
apic[97] rvp_.end(1)
rvp_.origin(0)
save_window_.addobject(rvp_, 5, 7, 0.8, 0.9)
maxica_graph[7]=save_window_
}
objectvar scene_vector_[1]
{doNotify()}

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