Skip to main content
Ctrl+K
NeuroML Documentation - Home

User documentation

  • Mission and Aims
  • How to use this documentation
  • Get NeuroML
  • Getting started with NeuroML
    • Simulating a regular spiking Izhikevich neuron
    • Interactive single Izhikevich neuron NeuroML example
    • A two population network of regular spiking Izhikevich neurons
    • Interactive two population network example
    • Simulating a single compartment Hodgkin-Huxley neuron
    • Interactive single compartment HH example
    • Simulating a multi compartment OLM neuron
    • Interactive multi-compartment OLM cell example
    • Create novel NeuroML models from components on NeuroML-DB
  • Finding and sharing NeuroML models
  • Creating NeuroML models
    • Converting models to NeuroML and sharing them on Open Source Brain
    • Handling Morphology Files
    • HDF5 support
    • Maintaining provenance in NeuroML models
  • Validating NeuroML Models
  • Visualising NeuroML Models
    • Visualising and analysing ion channel models
    • Visualising and analysing cell models
  • Simulating NeuroML Models
  • Optimising/fitting NeuroML Models
  • Testing/validating NeuroML Models
  • LEMS: Low Entropy Model Specification
    • Model structure overview
    • Example 1: Dimensions, Units, ComponentTypes and Components
    • Example 2: tidying up example 1
    • Example 3: Connection dependent synaptic components
    • Example 4: Kinetic schemes
    • Example 5: References and paths
    • Example 6: User defined types for simulation and display
    • Example 7: User defined types for networks and populations
    • Example 8: Regimes in Dynamics definitions
  • Schema/Specification
    • NeuroML v2
      • NeuroMLDocument
      • NeuroMLCoreDimensions
      • NeuroMLCoreCompTypes
      • Cells
      • Channels
      • Synapses
      • Inputs
      • Networks
      • PyNN
      • Simulation
      • Index
    • NeuroML v1
    • LEMS
      • Model structure
      • Units and dimensions
      • Defining component types
      • Dynamics
      • Structure
      • Simulation
      • Procedure
      • Defining Components
      • Geometry
  • NeuroML 2 and LEMS
    • Conventions
    • Units and dimensions
    • Paths
    • Quantities and recording
    • LEMS Simulation files
  • Extending NeuroML
  • Software and Tools
    • pyNeuroML
    • libNeuroML
    • pyLEMS
    • NeuroMLlite
    • jNeuroML
    • jLEMS
    • NeuroML C++ API
    • MatLab NeuroML Toolbox
    • Tools and resources with NeuroML support
      • Approaches to adding NeuroML support
      • NEURON and NeuroML
      • NetPyNE and NeuroML
      • PyNN and NeuroML
      • Brian and NeuroML
      • MOOSE and NeuroML
      • EDEN and NeuroML
      • Arbor and NeuroML
      • N2A and NeuroML
      • NEST and NeuroML
      • SWC and NeuroML
  • Citing NeuroML and related publications
  • Frequently asked questions (FAQ)
  • Walk throughs
    • Converting Ray et al 2020 to NeuroML
      • Setting up
      • Converting to NeuroML
      • Adding OMV tests

NeuroML events

  • NeuroML outreach and events
  • July 2024: NeuroML tutorial at CNS 2024
  • April 2024: NeuroML hackathon at HARMONY 2024
  • June 2022: NeuroML tutorial at CNS*2022 satellite tutorials
  • April 2022: NeuroML development workshop at HARMONY 2022
  • October 2021: NeuroML development workshop at COMBINE meeting
  • August 2021: NeuroML tutorial at INCF Training Weeks
  • July 2021: NeuroML tutorial at CNS*2021
  • March 2021: NeuroML hackathon at HARMONY 2021
  • March 2012: Fourth NeuroML Development Workshop
  • Past NeuroML Events

The NeuroML Initiative

  • Getting in touch
  • Overview of standards in neuroscience
  • A brief history of NeuroML
  • NeuroML Editorial Board
    • History of the NeuroML Editorial Board
    • Workshop and Meeting reports
  • NeuroML Scientific Committee
  • Funding and Acknowledgements
  • Outreach and training
  • NeuroML contributors
  • NeuroML repositories
  • Code of Conduct

Developer documentation

  • Overview
    • Contribution guidelines
    • Release Process
    • Making changes to the NeuroML standard
  • Interaction with other languages and standards

Reference

  • Glossary
  • Bibliography
  • Repository
  • Suggest edit
  • Open issue
  • .md

Citing NeuroML and related publications

Contents

  • Citing NeuroML
    • Papers
      • NeuroML 2 and LEMS
      • libNeuroML and PyLEMS
      • NeuroML v1
      • Open Source Brain
    • Software
  • Other publications
    • Book Chapters
    • Abstracts

Citing NeuroML and related publications#

This page documents how one can cite NeuroML in their work, and lists publications associated with the NeuroML initiative.

Citing NeuroML#

Please cite NeuroML in your work whenever you have used it. Generally, you should cite the particular paper while discussing NeuroML in the text, and also note and cite the specific version of the NeuroML tool that has been used in the work.

Papers#

Please cite the following papers as required:

NeuroML 2 and LEMS#

The main citation for NeuroML 2

Please cite the following paper when discussing NeuroML v2.0 or LEMS.

Cannon RC, Gleeson P, Crook S, Ganapathy G, Marin B, Piasini E and Silver RA (2014) LEMS: A language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2, Frontiers in Neuroinformatics 8: 79.

@Article{Cannon2014,
  author    = {Robert C. Cannon and Padraig Gleeson and Sharon Crook and Gautham Ganapathy and Boris Marin and Eugenio Piasini and R. Angus Silver},
  title     = {{LEMS}: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning {NeuroML} 2},
  doi       = {10.3389/fninf.2014.00079},
  volume    = {8},
  journal   = {Frontiers in Neuroinformatics},
  publisher = {Frontiers Media {SA}},
  year      = {2014},
}

libNeuroML and PyLEMS#

Citation for Python & NeuroML

Please cite the following paper when using the Python NeuroML libraries

Vella M, Cannon RC, Crook S, Davison AP, Ganapathy G, Robinson HP, Silver RA and Gleeson P (2014) libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience. Frontiers in Neuroinformatics 8: 38.

@Article{Vella2014,
  author       = {Vella, Michael and Cannon, Robert C. and Crook, Sharon and Davison, Andrew P. and Ganapathy, Gautham and Robinson, Hugh P. C. and Silver, R. Angus and Gleeson, Padraig},
  title        = {libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.},
  doi          = {10.3389/fninf.2014.00038},
  pages        = {38},
  volume       = {8},
  journal      = {Frontiers in neuroinformatics},
  year         = {2014},
}

NeuroML v1#

Citation for NeuroML v1

Please cite the following paper when discussing NeuroML version 1. (deprecated)

Gleeson, P., S. Crook, R. C. Cannon, M. L. Hines, G. O. Billings, et al. (2010) NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail. PLoS Computational Biology 6(6): e1000815.

@Article{Gleeson2010,
  author    = {Padraig Gleeson and Sharon Crook and Robert C. Cannon and Michael L. Hines and Guy O. Billings and Matteo Farinella and Thomas M. Morse and Andrew P. Davison and Subhasis Ray and Upinder S. Bhalla and Simon R. Barnes and Yoana D. Dimitrova and R. Angus Silver},
  title     = {{NeuroML}: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail},
  doi       = {10.1371/journal.pcbi.1000815},
  editor    = {Karl J. Friston},
  number    = {6},
  pages     = {e1000815},
  volume    = {6},
  journal   = {{PLoS} Computational Biology},
  publisher = {Public Library of Science ({PLoS})},
  year      = {2010},
}

Open Source Brain#

This paper describes version 1 of the Open Source Brain platform. Please cite this paper if you have made use of OSB in your work:

Gleeson P, Cantarelli M, Marin B, Quintana A, Earnshaw M, et al. (2019) Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits. Neuron 103 (3):395–411

@Article{Gleeson2019,
  author    = {Padraig Gleeson and Matteo Cantarelli and Boris Marin and Adrian Quintana and Matt Earnshaw and Sadra Sadeh and Eugenio Piasini and Justas Birgiolas and Robert C. Cannon and N. Alex Cayco-Gajic and Sharon Crook and Andrew P. Davison and Salvador Dura-Bernal and Andr{\'{a}}s Ecker and Michael L. Hines and Giovanni Idili and Frederic Lanore and Stephen D. Larson and William W. Lytton and Amitava Majumdar and Robert A. McDougal and Subhashini Sivagnanam and Sergio Solinas and Rokas Stanislovas and Sacha J. van Albada and Werner van Geit and R. Angus Silver},
  title     = {Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits},
  doi       = {10.1016/j.neuron.2019.05.019},
  number    = {3},
  pages     = {395--411},
  volume    = {103},
  journal   = {Neuron},
  publisher = {Elsevier {BV}},
  year      = {2019},
}

Software#

It is important to cite software used in scientific work to:

  • aid reproducibility of work

  • to ensure that the developers of tools receive credit for their work.

You can learn more about Software Citation Principles as set out by the F1000 Software Citation working group in this work [SKNG16].

You can obtain the version of pyNeuroML and associated tools using the following command (with example output):

$ pynml -version
pyNeuroML v0.5.20 (libNeuroML v0.3.1, jNeuroML v0.11.1)

Each NeuroML software tool has a unique DOI and reference associated with each release at the Zenodo archival facility. On each entry, you will be able to find the DOI and citation of the particular version you are using, and you will also be able to download the citation in different formats at the bottom of the right hand side bar.

Other publications#

This section lists other publications related to NeuroML.

Günay, C. et al. (2008) Computational intelligence in electrophysiology: Trends and open problems. In Smolinski, Milanova and Hassanien, eds. Applications of Computational Intelligence in Biology. Springer, Berlin/Heidelberg.

Gleeson, P., V. Steuber, and R. A. Silver (2007) neuroConstruct: A Tool for Modeling Networks of Neurons in 3D Space. Neuron. 54(2):219-235.

Cannon R. C., M. O. Gewaltig, P. Gleeson, U. S. Bhalla, H. Cornelis, M. L. Hines, F. W. Howell, E. Muller, J. R. Stiles, S. Wils, E. De Schutter (2007) Interoperability of Neuroscience Modeling Software: Current Status and Future Directions. Neuroinformatics Volume 5, 127-138.

Crook, S., P. Gleeson, F. Howell, J. Svitak and R.A. Silver (2007) MorphML: Level 1 of the NeuroML standards for neuronal morphology data and model specification. Neuroinformatics. 5(2):96-104.

Crook, S. and F. Howell (2007) XML for data representation and model specification in neuroscience. In Methods in Molecular Biology Book Series: Neuroinformatics. ed. C. Crasto, Humana Press.

Crook, S., D. Beeman, P. Gleeson and F. Howell (2005) XML for model specification in neuroscience: An introduction and workshop summary. Brains, Minds, and Media. 1:bmm228 (urn:nbn:de:0009-3-2282).

Qi, W. and S. Crook (2004) Tools for neuroinformatic data exchange: An XML application for neuronal morphology data. Neurocomputing. 58-60C:1091-1095.

Goddard, N., M. Hucka, F. Howell, H. Cornelis, K. Shankar and D. Beeman (2001) Towards NeuroML: Model description methods for collaborative modeling in neuroscience. Philosophical Transactions of the Royal Society B. 356:1209-1228.

Book Chapters#

Crook, SM, HE Plesser, AP Davison (2013) Lessons from the past: approaches for reproducibility in computational neuroscience. In JM Bower, ed. 20 Years of Computational Neuroscience, Springer

Gleeson, P, V Steuber, RA Silver and S Crook (2012) NeuroML. In Le Novere, ed. Computational Systems Biology, Springer.

Abstracts#

Cannon, R, P Gleeson, S Crook, RA Silver (2012) A declarative model specification system allowing NeuroML to be extended with user-defined component types. BMC Neuroscience. 13(Suppl 1): P42.

Gleeson P, S Crook, A Silver, R Cannon (2011) Development of NeuroML version 2.0: Greater extensibility, support for abstract neuronal models and interaction with Systems Biology languages. BMC Neuroscience. 12:P29.

Gleeson, P., S. Crook, S. Barnes and R.A. Silver (2008) Interoperable model components for biologically realistic single neuron and network models implemented in NeuroML. Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2008. doi: 10.3389/conf.neuro.11.2008.01.135.

Larson, S. and M. Martone (2008) A spatial framework for multi-scale computational neuroanatomy. Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2008. doi: 10.3389/conf.neuro.11.2008.01.134.

Crook, S., P. Gleeson and R.A. Silver (2007) NetworkML: Level 3 of the NeuroML standards for multiscale model specification and exchange. Society for Neuroscience Abstracts. 102.28.

Gleeson, P., S. Crook, V. Steuber and R.A. Silver (2007) Using NeuroML and neuroConstruct to build neuronal network models for multiple simulators. BMC Neuroscience. 8(2):P101.

previous

SWC and NeuroML

next

Frequently asked questions (FAQ)

Contents
  • Citing NeuroML
    • Papers
      • NeuroML 2 and LEMS
      • libNeuroML and PyLEMS
      • NeuroML v1
      • Open Source Brain
    • Software
  • Other publications
    • Book Chapters
    • Abstracts

By NeuroML contributors

© Copyright 2025.