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

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"… 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. …"
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:
Gene(s): Kv4.2 KCND2; Kv1.2 KCNA2; Cav1.3 CACNA1D; Cav1.2 CACNA1C; Kv2.1 KCNB1;
Simulation Environment: NEURON; Python;
Model Concept(s): Synaptic Plasticity; Signaling pathways; Calcium dynamics; Multiscale;
Implementer(s): Mattioni, Michele [mattioni at];
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;
import matplotlib.pyplot as plt
import os 

from helpers.plotter import DoublePlotter, StimulPlotter
import neuronvisio.manager

filename = 'storage.h5'

stimulated_spines = ['spine554', 'spine555', 'spine556', 
                     'spine558', 'spine559', 'spine560', 
                     'spine562', 'spine563', 'spine564', 
                     'spine1468', 'spine1469', 'spine1470', 
                     'spine1472', 'spine1473', 'spine1474', 
                     'spine1476', 'spine1477', 'spine1478']

#stimulated_spines = ['spine554']
dirs = {'cpm_8Hz' : 'Data_rmt/30-04-2011/Sim_0/',
        'cpm_20Hz' : 'Data_rmt/29-04-2011/Sim_2/',
        'cpm_40Hz' : 'Data_rmt/29-04-2011/Sim_1/',
        'cpm_50Hz' : 'Data_rmt/29-04-2011/Sim_0/',
        'cpm_40Hz_long' : 'Data_rmt/25-06-2011/Sim_0/',

def plotting(fig_fil):

for condition, dir in dirs.iteritems():
    h5_filename = dir + 'storage.h5'
    neuronvisio.manager = reload(neuronvisio.manager)
    name = 'ele_bio_' + condition + "_" + 'spine1478' + '.png'
    if not os.path.exists(os.path.join(dir, name)):
        man = neuronvisio.manager.Manager()
        dp = DoublePlotter()
        sp = StimulPlotter()
        for spine_num in stimulated_spines:
            name = None
            fig_filename = None
            name = 'ele_bio_' + condition + "_" + spine_num + '.png'
            fig_filename = os.path.join(dir, name)
            if not os.path.exists(fig_filename):
                biogroup = 'timeSeries_' + spine_num
                fig = plt.figure()
                ax1, ax2 = dp.plot_double_axes(man, spine_num, 'v', 
                    'AMPAR_P', bio_group=biogroup)
                ax1.set_ylim(-90, 0)
                ax2.set_ylim(10, 150) # make space for the legend.
                sp.plot_input(spine_num, man, ax=ax1)
                for ext in ['.png', '.pdf']:            
                    name = 'ele_bio_' + condition + "_" + spine_num + ext
                    fig_filename = os.path.join(dir, name)
                    print "Saved file %s" %fig_filename
                print "File %s exist. Skipping" %fig_filename
        del man
        print "Skipping dir %s" %dir

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