Simulation of calcium signaling in fine astrocytic processes (Denizot et al 2019)

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Accession:247694
This model corresponds to the model presented in Denizot et al, 2019. The model indicates that the frequency of calcium signals crucially depends on the spatial organization of the IP3R channels, including their clustering and co-localization with the other sources of calcium influx to the cytosol. Spontaneous calcium signals generated by the model with realistic PAPs volume and calcium concentration successfully reproduce spontaneous calcium transients that we measured in calcium micro-domains with confocal microscopy. To our knowledge, this model is the first model suited to the investigation of spontaneous calcium dynamics in fine astrocytic processes, a crucial step towards a better understanding of the spatio-temporal integration of astrocyte signals in response to neuronal activity.
Reference:
1 . Denizot A, Arizono M, Nägerl UV, Soula H, Berry H (2019) Simulation of calcium signaling in fine astrocytic processes: Effect of spatial properties on spontaneous activity. PLoS Comput Biol 15:e1006795 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Glia;
Brain Region(s)/Organism: Generic;
Cell Type(s): Astrocyte;
Channel(s):
Gap Junctions:
Receptor(s): IP3;
Gene(s):
Transmitter(s):
Simulation Environment: Python; STEPS; C or C++ program; XPP;
Model Concept(s): Signaling pathways; Calcium dynamics;
Implementer(s): Denizot, Audrey [audrey.denizot at inria.fr];
Search NeuronDB for information about:  IP3;
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DenizotEtAl_2019
Gillespie
ODE
Particle-based
STEPS
README
                            
This is the README file for the model associated with the paper:

Denizot, A., Arizono, M., Nägerl, V., Soula, H., Berry, H. (2019). Simulation of calcium signaling in fine astrocytic processes: effect of spatial properties on spontaneous activity. 


We present here 4 different implementations of the model, described below.


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##### Gillespie #####
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This model corresponds to the Gillespie implementation of the model. It has been developed in python. This model has been used in Figure 2.


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######## ODE ########
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This model corresponds to ODE model presented in Fig2 of the paper. It requires XPPAUT software, which is freely available at http://www.math.pitt.edu/~bard/xpp/xpp.html


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### Particle-based ###
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This model corresponds to the particle-based implementation of the model. It has been developed in C. This is the model used in Figures 2 to 5 of the paper.


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##### STEPS #####
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This model corresponds to the GCaMP6s model presented in Fig6 of the paper. It has been developed in python and requires STEPS software, which is freely available at http://steps.sourceforge.net/STEPS/default.php



Contact:
audrey.denizot@inria.fr