NetPyNE, a tool for data-driven multiscale modeling of brain circuits.

Autor:	Dura-Bernal S; Department of Physiology & Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States., Suter BA; Department of Physiology, Northwestern University, Chicago, United States., Gleeson P; Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom., Cantarelli M; MetaCell LLC, Boston, United States., Quintana A; EyeSeeTea Ltd, Cheltenham, United Kingdom., Rodriguez F; Department of Physiology & Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States.; MetaCell LLC, Boston, United States., Kedziora DJ; Complex Systems Group, School of Physics, University of Sydney, Sydney, Australia., Chadderdon GL; Department of Physiology & Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States., Kerr CC; Complex Systems Group, School of Physics, University of Sydney, Sydney, Australia., Neymotin SA; Department of Physiology & Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States.; Nathan Kline Institute for Psychiatric Research, Orangeburg, United States., McDougal RA; Department of Neuroscience and School of Medicine, Yale University, New Haven, United States.; Center for Medical Informatics, Yale University, New Haven, United States., Hines M; Department of Neuroscience and School of Medicine, Yale University, New Haven, United States., Shepherd GM; Department of Physiology, Northwestern University, Chicago, United States., Lytton WW; Department of Physiology & Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States.; Department of Neurology, Kings County Hospital, Brooklyn, United States.
Jazyk:	angličtina
Zdroj:	ELife [Elife] 2019 Apr 26; Vol. 8. Date of Electronic Publication: 2019 Apr 26.
DOI:	10.7554/eLife.44494
Abstrakt:	Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis - connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena. Competing Interests: SD, BS, PG, DK, GC, CK, SN, RM, MH, GS, WL No competing interests declared, MC, FR is affiliated with MetaCell LLC. The author has no other competing interests to declare. AQ is affiliated with EyeSeeTea Ltd. The author has no other competing interests to declare. (© 2019, Dura-Bernal et al.)
Databáze:	MEDLINE
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