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Computational Systems Neurobiology pp 489–517Cite as

NeuroML

Abstract

NeuroML is a language based on XML for describing detailed neuronal models, which can contain multiple active conductances and complex morphologies. Networks of such cells positioned and synaptically connected in 3D can also be described. In this chapter we present an overview of the history of NeuroML, a brief description of the current version of the language, plans for future developments and the relationship to other standardisation initiatives in the wider computational neuroscience field. We also present a list of NeuroML resources which are currently available, such as language specifications, services on the NeuroML website, examples of models in this format, simulation platform support, and other applications for generating and visualising highly detailed neuronal networks. These resources illustrate how NeuroML can be a key part of the toolchain for researchers addressing complex questions of neuronal system function.

Keywords

  • Neuronal Morphology
  • Computational Neuroscience
  • Spike Timing Dependent Plasticity
  • Neuroscience Information Framework
  • Synapse Model

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Fig. 16.1
Fig. 16.2
Fig. 16.3
Fig. 16.4
Fig. 16.5
Fig. 16.6
Fig. 16.7
Fig. 16.8
Fig. 16.9
Fig. 16.10
Fig. 16.11

Notes

  1. 1.

    http://www.neuroml.org

  2. 2.

    http://symphony.bu.edu

  3. 3.

    http://www.virtualratbrain.org

  4. 4.

    http://sourceforge.net/projects/neuroml

  5. 5.

    http://www.brainml.org

  6. 6.

    http://www.nineml.org

  7. 7.

    http://www.neuinfo.org

  8. 8.

    http://www.ebi.ac.uk/sbo

  9. 9.

    http://www.geneontology.org

  10. 10.

    http://www.neuroml.org/specifications

  11. 11.

    for example see http://neuroml.org/NeuroMLValidator/Latest.jsp?spec=MorphML

  12. 12.

    http://neuroml.svn.sourceforge.net/viewvc/neuroml

  13. 13.

    http://www.web3d.org/x3d

  14. 14.

    http://www.neuroml.org/neuron_tools

  15. 15.

    http://www.neuroml.org/neuron_tools

  16. 16.

    see http://www.neuroConstruct.org/docs/importneuron for more details

  17. 17.

    http://www.hdfgroup.org/products/hdf5_tools

  18. 18.

    http://www.neuroml.org/neuron_tools

  19. 19.

    http://www.lsm.tugraz.at/pcsim

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Acknowledgements

The NeuroML initiative has involved contributions from a large number of researchers over many years. Please see http://www.neuroml.org/contributors.php for full details on contributors. Support for PG and RAS came from the MRC (Program grant G0400598 to RAS and a Special Research Training Fellowship to PG), the BBSRC (005490), the EU (EUSynapse, LSHM-CT-2005-019055) and the Welcome Trust (086699 to RAS). RAS is in receipt of a Wellcome Senior Research Fellowship (064413). Contributions of SC were supported by NIH R01MH081905. Volker??

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Authors and Affiliations

  1. Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK

    Padraig Gleeson & R. Angus Silver

  2. School of Computer Science, Science and Technology Research Institute, University of Hertfordshire, Hatfield, UK

    Volker Steuber

  3. School of Mathematical and Statistical Sciences, School of Life Sciences, and Center for Adaptive Neural Systems, Arizona State University, Tempe, AZ, USA

    Sharon Crook

Authors
  1. Padraig Gleeson
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  2. Volker Steuber
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  3. R. Angus Silver
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  4. Sharon Crook
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Correspondence to Padraig Gleeson .

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Editors and Affiliations

  1. European Bioinformatics Institute, EMBL-Outstation-Hinxton, Wellcome Trust Genome Campus, Welcome-Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom

    N. Le Novère

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Gleeson, P., Steuber, V., Silver, R.A., Crook, S. (2012). NeuroML. In: Le Novère, N. (eds) Computational Systems Neurobiology. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3858-4_16

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