Multiscale simulation of the striatal medium spiny neuron (Mattioni & Le Novere 2013)

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Accession:150284
"… We present a new event-driven algorithm to synchronize different neuronal models, which decreases computational time and avoids superfluous synchronizations. The algorithm is implemented in the TimeScales framework. We demonstrate its use by simulating a new multiscale model of the Medium Spiny Neuron of the Neostriatum. The model comprises over a thousand dendritic spines, where the electrical model interacts with the respective instances of a biochemical model. Our results show that a multiscale model is able to exhibit changes of synaptic plasticity as a result of the interaction between electrical and biochemical signaling. …"
Reference:
1 . Mattioni M, Le Novère N (2013) Integration of biochemical and electrical signaling-multiscale model of the medium spiny neuron of the striatum. PLoS One 8:e66811 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse;
Brain Region(s)/Organism: Striatum;
Cell Type(s): Neostriatum medium spiny direct pathway GABA cell;
Channel(s): I Na,p; I Na,t; I T low threshold; I A; I K,Ca; I CAN; I Calcium; I A, slow; I Krp; I R; I Q;
Gap Junctions:
Receptor(s):
Gene(s): Kv4.2 KCND2; Kv1.2 KCNA2; Cav1.3 CACNA1D; Cav1.2 CACNA1C; Kv2.1 KCNB1;
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Synaptic Plasticity; Signaling pathways; Calcium dynamics; Multiscale;
Implementer(s): Mattioni, Michele [mattioni at ebi.ac.uk];
Search NeuronDB for information about:  Neostriatum medium spiny direct pathway GABA cell; I Na,p; I Na,t; I T low threshold; I A; I K,Ca; I CAN; I Calcium; I A, slow; I Krp; I R; I Q;
load_file("nrngui.hoc")

print "Testing mapping of SBML file BIOMD000000183_altered_id_replaced.xml on NEURON"

create soma
access soma
L = 1
diam = 1

insert pas  

insert BIOMD000000183_altered_id_replaced

psection()

tstop = 10.0
dt = 0.01
steps_per_ms = 100.000000

objref SampleGraph
SampleGraph = new Graph(0)

minVal = 0
maxVal = 10

{SampleGraph.size(0,tstop,minVal,maxVal)}
{SampleGraph.view(0, minVal, tstop, (maxVal-minVal), 100, 500, 500, 300)}
{
    SampleGraph.addexpr("soma.camR_Model_1(0.5)", 1, 1)
    SampleGraph.addexpr("soma.ca_Model_1(0.5)", 2, 1)
    SampleGraph.addexpr("soma.camR_ca1_A_Model_1(0.5)", 3, 1)
    SampleGraph.addexpr("soma.camR_ca1_B_Model_1(0.5)", 4, 1)
    SampleGraph.addexpr("soma.camR_ca1_C_Model_1(0.5)", 5, 1)
    SampleGraph.addexpr("soma.camR_ca1_D_Model_1(0.5)", 6, 1)
    SampleGraph.addexpr("soma.camR_ca2_AB_Model_1(0.5)", 7, 1)
    SampleGraph.addexpr("soma.camR_ca2_AC_Model_1(0.5)", 8, 1)
    SampleGraph.addexpr("soma.camR_ca2_AD_Model_1(0.5)", 9, 1)
    SampleGraph.addexpr("soma.camR_ca2_BC_Model_1(0.5)", 10, 1)
    SampleGraph.addexpr("soma.camR_ca2_BD_Model_1(0.5)", 11, 1)
    SampleGraph.addexpr("soma.camR_ca2_CD_Model_1(0.5)", 12, 1)
    SampleGraph.addexpr("soma.camR_ca3_ABC_Model_1(0.5)", 13, 1)
    SampleGraph.addexpr("soma.camR_ca3_ABD_Model_1(0.5)", 14, 1)
    SampleGraph.addexpr("soma.camR_ca3_ACD_Model_1(0.5)", 15, 1)
    SampleGraph.addexpr("soma.camR_ca3_BCD_Model_1(0.5)", 16, 1)
    SampleGraph.addexpr("soma.camR_ca4_ABCD_Model_1(0.5)", 17, 1)
    SampleGraph.addexpr("soma.camT_Model_1(0.5)", 18, 1)
    SampleGraph.addexpr("soma.camT_ca1_A_Model_1(0.5)", 19, 1)
    SampleGraph.addexpr("soma.camT_ca1_B_Model_1(0.5)", 20, 1)
    SampleGraph.addexpr("soma.camT_ca1_C_Model_1(0.5)", 21, 1)
    SampleGraph.addexpr("soma.camT_ca1_D_Model_1(0.5)", 22, 1)
    SampleGraph.addexpr("soma.camT_ca2_AB_Model_1(0.5)", 23, 1)
    SampleGraph.addexpr("soma.camT_ca2_AC_Model_1(0.5)", 24, 1)
    SampleGraph.addexpr("soma.camT_ca2_AD_Model_1(0.5)", 25, 1)
    SampleGraph.addexpr("soma.camT_ca2_BC_Model_1(0.5)", 26, 1)
    SampleGraph.addexpr("soma.camT_ca2_BD_Model_1(0.5)", 27, 1)
    SampleGraph.addexpr("soma.camT_ca2_CD_Model_1(0.5)", 28, 1)
    SampleGraph.addexpr("soma.camT_ca3_ABC_Model_1(0.5)", 29, 1)
    SampleGraph.addexpr("soma.camT_ca3_ABD_Model_1(0.5)", 30, 1)
    SampleGraph.addexpr("soma.camT_ca3_ACD_Model_1(0.5)", 31, 1)
    SampleGraph.addexpr("soma.camT_ca3_BCD_Model_1(0.5)", 32, 1)
    SampleGraph.addexpr("soma.camT_ca4_ABCD_Model_1(0.5)", 33, 1)
    SampleGraph.addexpr("soma.CaMKII_Model_1(0.5)", 34, 1)
    SampleGraph.addexpr("soma.camR_CaMKII_Model_1(0.5)", 35, 1)
    SampleGraph.addexpr("soma.camR_ca1_A_CaMKII_Model_1(0.5)", 36, 1)
    SampleGraph.addexpr("soma.camR_ca1_B_CaMKII_Model_1(0.5)", 37, 1)
    SampleGraph.addexpr("soma.camR_ca1_C_CaMKII_Model_1(0.5)", 38, 1)
    SampleGraph.addexpr("soma.camR_ca1_D_CaMKII_Model_1(0.5)", 39, 1)
    SampleGraph.addexpr("soma.camR_ca2_AB_CaMKII_Model_1(0.5)", 40, 1)
    SampleGraph.addexpr("soma.camR_ca2_AC_CaMKII_Model_1(0.5)", 41, 1)
    SampleGraph.addexpr("soma.camR_ca2_AD_CaMKII_Model_1(0.5)", 42, 1)
    SampleGraph.addexpr("soma.camR_ca2_BC_CaMKII_Model_1(0.5)", 43, 1)
    SampleGraph.addexpr("soma.camR_ca2_BD_CaMKII_Model_1(0.5)", 44, 1)
    SampleGraph.addexpr("soma.camR_ca2_CD_CaMKII_Model_1(0.5)", 45, 1)
    SampleGraph.addexpr("soma.camR_ca3_ABC_CaMKII_Model_1(0.5)", 46, 1)
    SampleGraph.addexpr("soma.camR_ca3_ABD_CaMKII_Model_1(0.5)", 47, 1)
    SampleGraph.addexpr("soma.camR_ca3_ACD_CaMKII_Model_1(0.5)", 48, 1)
    SampleGraph.addexpr("soma.camR_ca3_BCD_CaMKII_Model_1(0.5)", 49, 1)
    SampleGraph.addexpr("soma.camR_ca4_ABCD_CaMKII_Model_1(0.5)", 50, 1)
    SampleGraph.addexpr("soma.PP2B_Model_1(0.5)", 51, 1)
    SampleGraph.addexpr("soma.camR_PP2B_Model_1(0.5)", 52, 1)
    SampleGraph.addexpr("soma.camR_ca1_A_PP2B_Model_1(0.5)", 53, 1)
    SampleGraph.addexpr("soma.camR_ca1_B_PP2B_Model_1(0.5)", 54, 1)
    SampleGraph.addexpr("soma.camR_ca1_C_PP2B_Model_1(0.5)", 55, 1)
    SampleGraph.addexpr("soma.camR_ca1_D_PP2B_Model_1(0.5)", 56, 1)
    SampleGraph.addexpr("soma.camR_ca2_AB_PP2B_Model_1(0.5)", 57, 1)
    SampleGraph.addexpr("soma.camR_ca2_AC_PP2B_Model_1(0.5)", 58, 1)
    SampleGraph.addexpr("soma.camR_ca2_AD_PP2B_Model_1(0.5)", 59, 1)
    SampleGraph.addexpr("soma.camR_ca2_BC_PP2B_Model_1(0.5)", 60, 1)
    SampleGraph.addexpr("soma.camR_ca2_BD_PP2B_Model_1(0.5)", 61, 1)
    SampleGraph.addexpr("soma.camR_ca2_CD_PP2B_Model_1(0.5)", 62, 1)
    SampleGraph.addexpr("soma.camR_ca3_ABC_PP2B_Model_1(0.5)", 63, 1)
    SampleGraph.addexpr("soma.camR_ca3_ABD_PP2B_Model_1(0.5)", 64, 1)
    SampleGraph.addexpr("soma.camR_ca3_ACD_PP2B_Model_1(0.5)", 65, 1)
    SampleGraph.addexpr("soma.camR_ca3_BCD_PP2B_Model_1(0.5)", 66, 1)
    SampleGraph.addexpr("soma.camR_ca4_ABCD_PP2B_Model_1(0.5)", 67, 1)
    graphList[0].append(SampleGraph)
}

print "Starting simulation!"
{run()}
print "Finished simulation!"

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