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The SONATA Data Format for Efficient Description of Large-Scale Network Models

30 Pages Posted: 18 May 2019 Publication Status: Review Complete

See all articles by Kael Dai

Kael Dai

Allen Institute - Allen Institute for Brain Science

Juan Hernando

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Yazan N. Billeh

Allen Institute - Allen Institute for Brain Science

Sergey L. Gratiy

Allen Institute - Allen Institute for Brain Science

Judit Planas

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Andrew Davison

Université Paris-Sud - Paris-Saclay Institute of Neuroscience UMR 9197

Salvador Dura-Bernal

State University of New York (SUNY) - SUNY Downstate Medical Center

Padraig Gleeson

University College London - Department of Neuroscience, Physiology and Pharmacology

Adrien Devresse

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Michael Gevaert

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Werner A. H. Van Geit

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Arseny V. Povolotsky

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Eilif Muller

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Jean-Denis Courcol

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Anton Arkhipov

Allen Institute - Allen Institute for Brain Science

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Abstract

Increasing availability of comprehensive experimental datasets in neuroscience and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational network models. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. We provide reference Application Programming Interfaces and model examples to catalyze support and adoption of the format. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

Keywords: computational neuroscience, network models, high-performance computing, biologically realistic modeling, multiscale modeling, scientific software, standardization, reproducibility.

Suggested Citation

Dai, Kael and Hernando, Juan and Billeh, Yazan N. and Gratiy, Sergey L. and Planas, Judit and Davison, Andrew and Dura-Bernal, Salvador and Gleeson, Padraig and Devresse, Adrien and Gevaert, Michael and Van Geit, Werner A. H. and Povolotsky, Arseny V. and Muller, Eilif and Courcol, Jean-Denis and Arkhipov, Anton, The SONATA Data Format for Efficient Description of Large-Scale Network Models (May 14, 2019). Available at SSRN: https://ssrn.com/abstract=3387685 or http://dx.doi.org/10.2139/ssrn.3387685
This version of the paper has not been formally peer reviewed.

Kael Dai

Allen Institute - Allen Institute for Brain Science

615 Westlake Ave N
Seattle, WA 98109
United States

Juan Hernando

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Yazan N. Billeh

Allen Institute - Allen Institute for Brain Science ( email )

615 Westlake Ave N
Seattle, WA 98109
United States

Sergey L. Gratiy

Allen Institute - Allen Institute for Brain Science

615 Westlake Ave N
Seattle, WA 98109
United States

Judit Planas

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Andrew Davison

Université Paris-Sud - Paris-Saclay Institute of Neuroscience UMR 9197

Paris
France

Salvador Dura-Bernal

State University of New York (SUNY) - SUNY Downstate Medical Center

450 Clarkson Ave
Brooklyn, NY 11203
United States

Padraig Gleeson

University College London - Department of Neuroscience, Physiology and Pharmacology

London
United Kingdom

Adrien Devresse

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Michael Gevaert

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Werner A. H. Van Geit

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Arseny V. Povolotsky

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Eilif Muller

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Jean-Denis Courcol

École Polytechnique Fédérale de Lausanne - Blue Brain Project

Geneva
Switzerland

Anton Arkhipov (Contact Author)

Allen Institute - Allen Institute for Brain Science ( email )

615 Westlake Ave N
Seattle, WA 98109
United States

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