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; 
# IPython log file

def create_spine_name(spine_list):
    spine_sections_name = []
    for spine in spine_list:
        spine_sec_head = "spine%s_head" %spine
        spine_sec_neck = "spine%s_neck" %spine
        spine_sec_psd = "spine%s_psd" %spine
        spine_sections_name.append(spine_sec_head)
        spine_sections_name.append(spine_sec_neck)
        spine_sections_name.append(spine_sec_psd)
    return spine_sections_name




if __name__ == "__main__":

    spines_stimulated = [554, 555, 556, 558, 559, 560, 562, 563, 564, 
                  1468, 1469, 1470, 1472, 1473, 1474, 1476, 1477, 
                  1478]
    spines_second_train = [555, 559, 563, 1469, 1476, 1473]
    
    spines_sections_name = create_spine_name(spines_stimulated)
    spines_second_train_name = create_spine_name(spines_second_train)
    
    scalar_value = []
    
    for spine_sec in spines_sections_name:
        if spine_sec in spines_second_train_name:
            scalar_value.append(1)
        else:
            scalar_value.append(0.5)
            
    print "Now run: "
    print "controls.visio.select_sections(spines_sections_name, scalar_value)"

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