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MorphML: Level 1 of the NeuroML Standards for Neuronal Morphology Data and Model Specification

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Abstract

Quantitative neuroanatomical data are important for the study of many areas of neuroscience, and the complexity of problems associated with neuronal structure requires that research from multiple groups across many disciplines be combined. However, existing neuron-tracing systems, simulation environments, and tools for the visualization and analysis of neuronal morphology data use a variety of data formats, making it difficult to exchange data in a readily usable way. The NeuroML project was initiated to address these issues, and here we describe an extensible markup language standard, MorphML, which defines a common data format for neuronal morphology data and associated metadata to facilitate data and model exchange, database creation, model publication, and data archiving. We describe the elements of the standard in detail and outline the mappings between this format and those used by a number of popular applications for reconstruction, simulation, and visualization of neuronal morphology.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, School of Life Sciences, and Center for Adaptive Neural Systems, Arizona State University, Tempe, AZ, USA

    Sharon Crook

  2. Department of Physiology, University College London, London, UK

    Padraig Gleeson & R. Angus Silver

  3. Institute of Adaptive and Neural Computation, University of Edinburgh, Edinburgh, UK

    Fred Howell

  4. Research Imaging Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA

    Joseph Svitak

Authors
  1. Sharon Crook
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  2. Padraig Gleeson
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  3. Fred Howell
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  4. Joseph Svitak
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  5. R. Angus Silver
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Correspondence to Sharon Crook.

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Crook, S., Gleeson, P., Howell, F. et al. MorphML: Level 1 of the NeuroML Standards for Neuronal Morphology Data and Model Specification. Neuroinform 5, 96–104 (2007). https://doi.org/10.1007/s12021-007-0003-6

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  • DOI: https://doi.org/10.1007/s12021-007-0003-6

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