CA1 pyramidal neuron: synaptically-induced bAP predicts synapse location (Sterratt et al. 2012)

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Accession:144490
This is an adaptation of Poirazi et al.'s (2003) CA1 model that is used to measure BAP-induced voltage and calcium signals in spines after simulated Schaffer collateral synapse stimulation. In the model, the peak calcium concentration is highly correlated with soma-synapse distance under a number of physiologically-realistic suprathreshold stimulation regimes and for a range of dendritic morphologies. There are also simulations demonstrating that peak calcium can be used to set up a synaptic democracy in a homeostatic manner, whereby synapses regulate their synaptic strength on the basis of the difference between peak calcium and a uniform target value.
Reference:
1 . Sterratt DC, Groen MR, Meredith RM, van Ooyen A (2012) Spine calcium transients induced by synaptically-evoked action potentials can predict synapse location and establish synaptic democracy. PLoS Comput Biol 8:e1002545 [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 T low threshold; I A; I K; I M; I Mixed; I R; I_AHP;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Synaptic Plasticity;
Implementer(s): Sterratt, David ; Groen, Martine R [martine.groen at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; AMPA; NMDA; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I Mixed; I R; I_AHP;
/
bpap
CA1_multi
morphology
old20100419cell1
apical-non-trunk-list.hoc *
apical-trunk-list.hoc *
axonpoirazi.hoc *
axon-sec-list.hoc *
basal-paths.hoc *
basal-tree-list.hoc *
cell.hoc *
cell-analysis.hoc
gabab-gabaa-uniform-ratio.hoc *
n123.hoc *
nmda-ampa-ratio.hoc *
oblique-paths.hoc *
old20100419cell1_top.hoc
old20100419cell1_topadj.hoc
soma-list.hoc *
                            
{create axonseg[10]}

{soma connect axonseg[0](0), 1}
{access axonseg[0]}
{pt3dclear()}
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{pt3dadd(0.378,6.182,17.047,1.48)}
{pt3dadd(-2.565,6.418,18.439,1.1)}
{pt3dadd(-2.892,6.655,18.4,1.1)}
{pt3dadd(-3.062,6.689,18.4,1.1)}

{axonseg[0] connect axonseg[1](0), 1}
{access axonseg[1]}
{pt3dclear()}
{pt3dadd(-3.062,6.689,18.4,1.1)}
{pt3dadd(-4.757,11.446,9.12,1.1)}

{axonseg[1] connect axonseg[2](0), 1}
{access axonseg[2]}
{pt3dclear()}
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{pt3dadd(-20.26,22.034,6,1.1)}

{axonseg[1] connect axonseg[3](0), 1}
{access axonseg[3]}
{pt3dclear()}
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{pt3dadd(1.604,12.305,60.64,1.74)}
{pt3dadd(1.954,12.836,60.64,1.74)}
{pt3dadd(2.847,14.057,60.64,1.74)}
{pt3dadd(2.497,13.706,60.4,1.74)}

{axonseg[3] connect axonseg[4](0), 1}
{access axonseg[4]}
{pt3dclear()}
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{pt3dadd(3.74,15.469,64,0.8)}
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{axonseg[4] connect axonseg[5](0), 1}
{access axonseg[5]}
{pt3dclear()}
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{pt3dadd(112.92,140.346,32.159,0.8)}

{axonseg[5] connect axonseg[6](0), 1}
{access axonseg[6]}
{pt3dclear()}
{pt3dadd(112.92,140.346,32.159,0.8)}
{pt3dadd(112.92,140.346,32.199,0.48)}
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{pt3dadd(112.807,143.125,32.88,0.48)}
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{pt3dadd(113.293,145.894,35.28,0.48)}
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{axonseg[6] connect axonseg[7](0), 1}
{access axonseg[7]}
{pt3dclear()}
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{pt3dadd(112.864,153.985,33.44,0.48)}
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{pt3dadd(122.706,161.533,32.4,0.48)}
{pt3dadd(126.48,161.397,35.2,0.48)}
{pt3dadd(127.283,161.793,35.12,0.48)}
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{pt3dadd(136.131,166.833,35.04,0.48)}
{pt3dadd(136.074,167.556,35.04,0.48)}

{axonseg[6] connect axonseg[8](0), 1}
{access axonseg[8]}
{pt3dclear()}
{pt3dadd(111.09,148.775,32.24,0.48)}
{pt3dadd(111.09,148.775,32.96,0.48)}
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{axonseg[5] connect axonseg[9](0), 1}
{access axonseg[9]}
{pt3dclear()}
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{pt3dadd(274.443,218.734,29.92,0.48)}
{pt3dadd(275.584,219.061,29.92,0.48)}
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{pt3dadd(279.9,219.909,29.52,0.48)}
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{pt3dadd(285.291,220.745,30.24,0.48)}
{pt3dadd(289.347,222.169,29.04,0.48)}
{pt3dadd(289.234,222.542,29.04,0.48)}

objref axon_sec_list
axon_sec_list = new SectionList()

forsec "axonseg"{
  print secname()
  axon_sec_list.append()
}

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