The complexity of problems associated with structure and function in neuroscience requires that research from multiple groups across many disciplines be combined. In order to combine research from multiple groups, there must be an infrastructure for exchanging model specifications;however, the current use of multiple formats for encoding model information has hampered model exchange. NeuroML is an eXtensible Markup Language (XML) specification that was created to facilitate data archiving, data and model exchange, database creation, and model publication in the neurosciences. One of the goals of the NeuroML project is to develop standards for model specification that will allow for greater simulator interoperability and model exchange. The declarative specifications produced by the NeuroML standards project are arranged into levels, with higher levels adding extra concepts. Level 1 deals with neuroanatomical information and metadata. Level 2 allows for specification of cell models with realistic channel and synaptic mechanisms distributed on their membranes, and Level 3 describes networks of these cells in three dimensions.
The specific aims of the proposed neuroinformatic activities are as follows: 1) the NeuroML standards will be extended to accommodate models of biomolecular interactions and will be linked to the Systems Biology Markup Language (SBML) in order to create an XML specification for multiscale models in neuroscience, 2) all levels of the NeuroML standards and associated tools will be extended and linked to other neuroinformatic efforts, and 3) within the context of both published studies and the PI's current research collaborations, modeling studies will be used to generate examples of the use of NeuroML and to test the schema design, tools, and compatibility with GENESIS, NEURON, and other appropriate model simulation platforms.
Building working models of neurons and neural circuits is one of the best ways of furthering our understanding of how the nervous system works and what goes wrong following neural trauma or disease. The investigators propose to continue the development of a markup language specification for computational neuroscience, NeuroML, which will serve as a common data format for many applications including those necessary for simulating models. They will also continue their development of tools for validation of NeuroML documents, for document exchange, for import/export of model specifications in NeuroML, and for conversion of submitted NeuroML document files into simulator scripts or HTML format.
| Samavat, Mohammad; Luli, Dori; Crook, Sharon (2016) Neuronal Network Models for Sensory Discrimination. Conf Rec Asilomar Conf Signals Syst Comput 2016:1066-1073 |
| Tripathy, Shreejoy J; Burton, Shawn D; Geramita, Matthew et al. (2015) Brain-wide analysis of electrophysiological diversity yields novel categorization of mammalian neuron types. J Neurophysiol 113:3474-89 |
| Cannon, Robert C; Gleeson, Padraig; Crook, Sharon et al. (2014) LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2. Front Neuroinform 8:79 |
| Gleeson, Padraig; Crook, Sharon; Cannon, Robert C et al. (2010) NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS Comput Biol 6:e1000815 |
