1. Computational and Systems Biology
  2. Neuroscience

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

  1. Salvador Dura-Bernal  Is a corresponding author
  2. Benjamin A Suter
  3. Padraig Gleeson
  4. Matteo Cantarelli
  5. Adrian Quintana
  6. Facundo Rodriguez
  7. David J Kedziora
  8. George L Chadderdon
  9. Cliff C Kerr
  10. Samuel A Neymotin
  11. Robert A McDougal
  12. Michael Hines
  13. Gordon M G Shepherd
  14. William W Lytton
  1. State University of New York Downstate Medical Center, United States
  2. Northwestern University, United States
  3. University College London, United Kingdom
  4. Metacell LLC, United States
  5. EyeSeeTea Ltd, United Kingdom
  6. University of Sydney, Australia
  7. Yale University, United States
https://doi.org/10.7554/eLife.44494
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Cite this article
  1. Salvador Dura-Bernal
  2. Benjamin A Suter
  3. Padraig Gleeson
  4. Matteo Cantarelli
  5. Adrian Quintana
  6. Facundo Rodriguez
  7. David J Kedziora
  8. George L Chadderdon
  9. Cliff C Kerr
  10. Samuel A Neymotin
  11. Robert A McDougal
  12. Michael Hines
  13. Gordon M G Shepherd
  14. William W Lytton
(2019)
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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  3. Download .RIS

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

  1. Salvador Dura-Bernal

    Department of Physiology and Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States
    For correspondence
    salvadordura@gmail.com
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8561-5324

  2. Benjamin A Suter

    Department of Physiology, Northwestern University, Chicago, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9885-6936

  3. Padraig Gleeson

    Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5963-8576

  4. Matteo Cantarelli

    Metacell LLC, Boston, United States
    Competing interests
    Matteo Cantarelli, is affiliated with Metacell LLC. The author has no other competing interests to declare..

  5. Adrian Quintana

    EyeSeeTea Ltd, Cheltenham, United Kingdom
    Competing interests
    Adrian Quintana, is affiliated with EyeSeeTea Ltd. The author has no other competing interests to declare..

  6. Facundo Rodriguez

    Department of Physiology and Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States
    Competing interests
    No competing interests declared.

  7. David J Kedziora

    Complex Systems Group, School of Physics, University of Sydney, Sydney, Australia
    Competing interests
    No competing interests declared.

  8. George L Chadderdon

    Department of Physiology and Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States
    Competing interests
    No competing interests declared.

  9. Cliff C Kerr

    Complex Systems Group, School of Physics, University of Sydney, Sydney, Australia
    Competing interests
    No competing interests declared.

  10. Samuel A Neymotin

    Department of Physiology and Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States
    Competing interests
    No competing interests declared.

  11. Robert A McDougal

    Department of Neuroscience, Yale University, New Haven, United States
    Competing interests
    No competing interests declared.

  12. Michael Hines

    Department of Neuroscience, Yale University, New Haven, United States
    Competing interests
    No competing interests declared.

  13. Gordon M G Shepherd

    Department of Physiology, Northwestern University, Chicago, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1455-8262

  14. William W Lytton

    Department of Physiology and Pharmacology, State University of New York Downstate Medical Center, Brooklyn, United States
    Competing interests
    No competing interests declared.

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

  1. Upinder Singh Bhalla, Tata Institute of Fundamental Research, India

Version history

  1. Received: December 19, 2018
  2. Accepted: April 25, 2019
  3. Accepted Manuscript published: April 26, 2019 (version 1)
  4. Version of Record published: May 24, 2019 (version 2)
  5. 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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  1. Salvador Dura-Bernal
  2. Benjamin A Suter
  3. Padraig Gleeson
  4. Matteo Cantarelli
  5. Adrian Quintana
  6. Facundo Rodriguez
  7. David J Kedziora
  8. George L Chadderdon
  9. Cliff C Kerr
  10. Samuel A Neymotin
  11. Robert A McDougal
  12. Michael Hines
  13. Gordon M G Shepherd
  14. William W Lytton
(2019)
NetPyNE, a tool for data-driven multiscale modeling of brain circuits
eLife 8:e44494.
https://doi.org/10.7554/eLife.44494

Share this article

https://doi.org/10.7554/eLife.44494

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