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ModelView for ModelDB: Online Presentation of Model Structure

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Abstract

ModelDB (modeldb.yale.edu), a searchable repository of source code of more than 950 published computational neuroscience models, seeks to promote model reuse and reproducibility. Code sharing is a first step; however, model source code is often large and not easily understood. To aid users, we have developed ModelView, a web application for ModelDB that presents a graphical view of model structure augmented with contextual information for NEURON and NEURON-runnable (e.g. NeuroML, PyNN) models. Web presentation provides a rich, simulator-independent environment for interacting with graphs. The necessary data is generated by combining manual curation, text-mining the source code, querying ModelDB, and simulator introspection. Key features of the user interface along with the data analysis, storage, and visualization algorithms are explained. With this tool, researchers can examine and assess the structure of hundreds of models in ModelDB in a standardized presentation without installing any software, downloading the model, or reading model source code.

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References

  • Crockford, D. (2006). The application/json media type for JavaScript object notation (JSON).

  • Davison, A.P., Brüderle, D., Eppler, J., Kremkow, J., Muller, E., Pecevski, D., Perrinet, L., & Yger, P. (2008). PyNN: a common interface for neuronal network simulators. Frontiers in Neuroinformatics, 2.

  • Davison, A.P., Mattioni, M., Samarkanov, D., & Sumatra, T.B. (2014). A toolkit for reproducible research. In V. Stodden, F. Leisch, & R.D. Peng (Eds.) Implementing reproducible, research (pp. 57–79). Boca Raton: Chapman & Hall/CRC.

  • Gleeson, P., Steuber, V., & Silver, R.A. (2007). Neuroconstruct: a tool for modeling networks of neurons in 3D space. Neuron, 54(2), 219–235.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Gleeson, P., Crook, S., Cannon, R.C., Hines, M.L., Billings, G.O., Farinella, M., Morse, T.M., Davison, A.P., Ray, S., Bhalla, U.S., Barnes, S.R., Dimitrova, Y.D., & Silver, R.A. (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  PubMed Central  PubMed  Google Scholar 

  • Hines, M.L., & Carnevale, N.T. (2001). NEURON: a tool for neuroscientists. The Neuroscientist, 7, 123–135.

    Article  CAS  PubMed  Google Scholar 

  • Hines, M.L., Morse, T.M., & Carnevale, N.T. (2007). Model structural analysis in NEURON. Methods in Molecular Biology, 401, 91–102.

    Article  PubMed Central  PubMed  Google Scholar 

  • Kohn, M.C., Hines, M.L., Kootsey, J.M., & Feezor, M.D. (1994). A block organized model builder. Mathematical and Computer Modelling, 19(6), 75–97.

    Article  Google Scholar 

  • Le Novere, N., Bornstein, B., Broicher, A., Courtot, M., Donizelli, M., Dharuri, H., Li, L., Sauro, H., Schilstra, M., Shapiro, B., Snoep, J.L., & Hucka, M. (2006). BioModels database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Research, 34(suppl 1), D689–D691.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • McDougal, R.A., Hines, M.L., & Lytton, W.W. (2013). Reaction-diffusion in the NEURON simulator. Front Neuroinf, 7, 28.

    Article  Google Scholar 

  • Migliore, M., Hoffman, D.A., Magee, J.C., & Johnston, D. (1999). Role of an A-type K+ conductance in the back-propagation of action potentials in the dendrites of hippocampal pyramidal neurons. Journal of Computational Neuroscience, 7, 5–15.

    Article  CAS  PubMed  Google Scholar 

  • Migliore, M., Morse, T.M., Davison, A.P., Marenco, L., Shepherd, G.M., & Hines, M.L. (2003). ModelDB: making models publicly accessible to support computational neuroscience. Neuroinformatics, 1, 135–139.

    Article  PubMed Central  PubMed  Google Scholar 

  • Morse, T.M., Carnevale, N.T., Mutalik, P.G., Migliore, M., & Shepherd, G.M. (2010). Abnormal excitability of oblique dendrites implicated in early Alzheimer’s: a computational study. Frontiers in Neural Circuits, 4, 16.

    PubMed Central  PubMed  Google Scholar 

  • Podlaski, W.F., Ranjan, R., Seeholzer, Markram, H., Gerstner, W., & Vogels, T. (2013). Visualizing the similarity and pedigree of NEURON ion channel models available on ModelDB. Program No. 678.31. Neuroscience 2013 Abstracts. San Diego: Society for Neuroscience. Online.

  • Rivest, R. (1992). The MD5 message-digest algorithm. RFC1321, Internet engineering task force.

  • Usui, S. (2003). Visiome: neuroinformatics research in vision project. Neural Networks, 16(9), 1293–1300.

    Article  PubMed  Google Scholar 

  • Vervaeke, K., Lorincz, A., Gleeson, P., Farinella, M., Nusser, Z., & Silver, R.A. (2010). Rapid desynchronization of an electrically coupled interneuron network with sparse excitatory synaptic input. Neuron, 67, 435–451.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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Acknowledgments

We thank the laboratory of GM Shepherd for valuable suggestions for improving ModelView’s usability, P. Miller, L. Marenco, and N.T. Carnevale for comments on the manuscript, and Nicole Flokos for her contributions to the NeuronWeb library. This research was supported by NIH T15 LM007056, NIH R01 NS11613, and NIH R01 DC009977.

Conflict of interests

The authors declare that they have no conflict of interest.

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Correspondence to Robert A. McDougal.

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This work was supported in part by NIH grants R01 DC009977 and R01 NS011613, and by NIH grant T15 LM007056 from the National Library of Medicine.

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McDougal, R.A., Morse, T.M., Hines, M.L. et al. ModelView for ModelDB: Online Presentation of Model Structure. Neuroinform 13, 459–470 (2015). https://doi.org/10.1007/s12021-015-9269-2

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  • DOI: https://doi.org/10.1007/s12021-015-9269-2

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