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]
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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")}
objectvar save_window_, rvp_
objectvar scene_vector_[4]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}

//Begin PointProcessManager
{
load_file("pointman.hoc")
}
{
MSP_Cell[0].soma ocbox_ = new PointProcessManager(0)
}
{object_push(ocbox_)}
{
mt.select("IClamp") i = mt.selected()
ms[i] = new MechanismStandard("IClamp")
ms[i].set("del", 100, 0)
ms[i].set("dur", 500, 0)
ms[i].set("amp", 0.2481, 0)
mt.select("IClamp") i = mt.selected() maction(i)
hoc_ac_ = 0.5
sec.sec move() d1.flip_to(0)
}
{object_pop() doNotify()}
{
ocbox_ = ocbox_.v1
ocbox_.map("PointProcessManager", 7, 494, 208.32, 326.4)
}
objref ocbox_
//End PointProcessManager

{
xpanel("RunControl", 0)
v_init = -87.75
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
runStopAt = 5
xvalue("Continue til","runStopAt", 1,"{continuerun(runStopAt) stoprun=1}", 1, 1 )
runStopIn = 1
xvalue("Continue for","runStopIn", 1,"{continuerun(t + runStopIn) stoprun=1}", 1, 1 )
xbutton("Single Step","steprun()")
t = 198.019
xvalue("t","t", 2 )
tstop = 800
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 1.2589
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 40
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
screen_update_invl = 0.25
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
realtime = 2.33
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(2,100)
}
{
save_window_ = new Graph(0)
save_window_.size(0,840,-90,30)
scene_vector_[3] = save_window_
{save_window_.view(0, -90, 840, 120, 304, 104, 814.08, 319.36)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("MSP_Cell[0].soma.v(0.5)", 2, 1, 0.69047, 0.981953, 2)
}

//Begin VariableTimeStep
{
ocbox_ = NumericalMethodPanel[0]
}
{object_push(ocbox_)}
{
atol_ = 0.001  CVode[0].atol(atol_)
restore(301, 1)
}
{object_pop()}
{
ocbox_.map("VariableTimeStep", 233, 492, 277.44, 113.28)
}
objref ocbox_
//End VariableTimeStep

objectvar scene_vector_[1]
{doNotify()}