NetPyNE, a tool for data-driven multiscale modeling of brain circuits
- State University of New York Downstate Medical Center, United States
- Northwestern University, United States
- University College London, United Kingdom
- Metacell LLC, United States
- EyeSeeTea Ltd, United Kingdom
- University of Sydney, Australia
- Yale University, United States
Abstract
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, e.g. 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.
Data availability
All data and models used in this work are publicly available from the following GitHub and ModelDB links:- Fig 3: https://github.com/Neurosim-lab/netpyne/tree/paper/examples/paper/fig3- Fig 5: https://github.com/Neurosim-lab/netpyne/tree/paper/examples/paper/fig5- Fig 6: https://github.com/Neurosim-lab/netpyne/tree/paper/examples/paper/fig6- Fig 7: https://github.com/Neurosim-lab/netpyne/tree/paper/examples/paper/fig7- Fig 8: https://github.com/Neurosim-lab/netpyne/tree/paper/examples/paper/fig8- Fig 9A: https://github.com/ceciliaromaro/PD_in_NetPyNE- Fig 9B: https://github.com/rtekin/myKnoxRepo- Fig 9C: https://github.com/rodriguez-facundo/LASCON-project- Fig 9D: https://github.com/angietep/CA1-NetPyNE-modelTable 1:Dentate gyrus:- Original: https://modeldb.yale.edu/155568- NetPyNE: https://github.com/rodriguez-facundo/LASCON-projectCA1 microcircuits:- Original: https://modeldb.yale.edu/123815- NetPyNE: https://github.com/angietep/CA1-NetPyNE-modelEpilepsy in thalamocortex:- Original: https://modeldb.yale.edu/234233- NetPyNE: https://github.com/rodriguez-facundo/LASCON-projectEEG and MEG in cortex / HNN model:- Original: https://github.com/jonescompneurolab/hnn- NetPyNE: https://github.com/jonescompneurolab/hnn/tree/netpyneMotor cortex with RL: - Original: https://modeldb.yale.edu/183014- NetPyNE: https://github.com/Neurosim-lab/netpyne/tree/development/examples/RL_armCortical microcircuits:- Original: https://github.com/OpenSourceBrain/PotjansDiesmann2014/tree/master/PyNEST- NetPyNE: https://github.com/ceciliaromaro/PD_in_NetPyNE
Article and author information
Author details
Salvador Dura-Bernal
Gordon M G Shepherd
Funding
National Institute of Biomedical Imaging and Bioengineering (U01EB017695)
- Salvador Dura-Bernal
- Benjamin A Suter
- Matteo Cantarelli
- Adrian Quintana
- Facundo Rodriguez
- Samuel A Neymotin
- Michael Hines
- Gordon M G Shepherd
- William W Lytton
New York State Department of Health (DOH01-C32250GG-3450000)
- Salvador Dura-Bernal
- Facundo Rodriguez
- William W Lytton
Wellcome (101445)
- Padraig Gleeson
National Institute of Biomedical Imaging and Bioengineering (2R01DC012947-06A1)
- Samuel A Neymotin
National Institute of Biomedical Imaging and Bioengineering (R01EB022903)
- Salvador Dura-Bernal
- Michael Hines
- William W Lytton
National Institute of Biomedical Imaging and Bioengineering (R01MH086638)
- Robert A McDougal
- Michael Hines
- William W Lytton
Wellcome (212941)
- Padraig Gleeson
National Institute of Biomedical Imaging and Bioengineering (3R01EB022889)
- Salvador Dura-Bernal
- Matteo Cantarelli
- Adrian Quintana
- Facundo Rodriguez
- Samuel A Neymotin
- Michael Hines
Australian Research Council (DE140101375)
- David J Kedziora
- Cliff C Kerr
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Upinder Singh Bhalla, Tata Institute of Fundamental Research, India
Version history
- Received: December 19, 2018
- Accepted: April 25, 2019
- Accepted Manuscript published: April 26, 2019 (version 1)
- Version of Record published: May 24, 2019 (version 2)
- Version of Record updated: May 31, 2019 (version 3)
Copyright
© 2019, Dura-Bernal et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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NetPyNE, a tool for data-driven multiscale modeling of brain circuits
eLife 8:e44494.
https://doi.org/10.7554/eLife.44494
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