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DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by eq...

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Autores principales: Sherfey, Jason S., Soplata, Austin E., Ardid, Salva, Roberts, Erik A., Stanley, David A., Pittman-Polletta, Benjamin R., Kopell, Nancy J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862864/
https://www.ncbi.nlm.nih.gov/pubmed/29599715
http://dx.doi.org/10.3389/fninf.2018.00010
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author Sherfey, Jason S.
Soplata, Austin E.
Ardid, Salva
Roberts, Erik A.
Stanley, David A.
Pittman-Polletta, Benjamin R.
Kopell, Nancy J.
author_facet Sherfey, Jason S.
Soplata, Austin E.
Ardid, Salva
Roberts, Erik A.
Stanley, David A.
Pittman-Polletta, Benjamin R.
Kopell, Nancy J.
author_sort Sherfey, Jason S.
collection PubMed
description DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.
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spelling pubmed-58628642018-03-29 DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation Sherfey, Jason S. Soplata, Austin E. Ardid, Salva Roberts, Erik A. Stanley, David A. Pittman-Polletta, Benjamin R. Kopell, Nancy J. Front Neuroinform Neuroscience DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. Frontiers Media S.A. 2018-03-15 /pmc/articles/PMC5862864/ /pubmed/29599715 http://dx.doi.org/10.3389/fninf.2018.00010 Text en Copyright © 2018 Sherfey, Soplata, Ardid, Roberts, Stanley, Pittman-Polletta and Kopell. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Sherfey, Jason S.
Soplata, Austin E.
Ardid, Salva
Roberts, Erik A.
Stanley, David A.
Pittman-Polletta, Benjamin R.
Kopell, Nancy J.
DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
title DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
title_full DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
title_fullStr DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
title_full_unstemmed DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
title_short DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation
title_sort dynasim: a matlab toolbox for neural modeling and simulation
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862864/
https://www.ncbi.nlm.nih.gov/pubmed/29599715
http://dx.doi.org/10.3389/fninf.2018.00010
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