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The Modeler’s Workspace

Making Model-Based Studies of the Nervous System More Accessible

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Computational Neuroanatomy
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Abstract

A realistic neuronal model represents a modeler’ s understanding of the structure and function of a part of the nervous system. The increasing number of such models represents a significant accumulation of knowledge about the structural and functional organization of nervous systems. However, locating appropriate models and interpreting them becomes increasingly more difficult as the number of online model and experimental databases grows. The central motivation for the Modeler’s Workspace project is to address these problems.

The Modeler’ s Workspace is a collection of software tools being created to enable users to interact with databases of models and data. It will provide facilities for: searching multiple remote databases for model components based on various criteria; visualizing the characteristics of the components retrieved; creating new components, either from scratch or derived from existing models; combining components into new models; linking models to experimental data as well as online publications; and interacting with simulation packages such as GENESIS to simulate the new constructs. It is being written in Java for portability and extensibility. It is modular in design and uses pluggable components. To increase the probability that the Modeler’s Workspace will be compatible with future databases and tools, we are using the XML, the eXtensible Markup Language, as the interchange format for communicating with databases.

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References

  1. Forss J, Beeman D, Eichler-West R, Bower JM. The Modeler’s Workspace: A distributed digital library for neuroscience. Future Generation Computer Systems 1999; 16: 111–121.

    Article  Google Scholar 

  2. Bower JM, Beeman D. The Book of GENESIS: Exploring Realistic Neural Models with the GEneral NEural SImulation System, 2nd ed. Springer-Verlag, New York, 1998.

    Google Scholar 

  3. Hines M, Carnevale NT. The NEURON simulation environment. Neural Computation 1997; 9: 1179–1209.

    Article  PubMed  CAS  Google Scholar 

  4. Ermentrout GB. XPP-Aut:X-windows PhasePlane plus Auto. http://www.math.pitt.edu/bard/xpp/xpp.html. 2000.

  5. Goddard N, Hood G, Howell F, Hines M, De Schutter E. 2001. NEOSIM: portable plug and play neuronal modelling. Neurocomputing, 2001; 38–40: 1657–1661.

    Article  Google Scholar 

  6. Arnold K, Gosling J. The Java Programming Language. Addison-Wesley, Reading, MA, 1997.

    Google Scholar 

  7. Bosak J, Bray T. XML and the second-generation web. Sci Am 1999; 280: 89–93.

    Article  Google Scholar 

  8. Koslow SH, Huerta MF. (eds) Neuroinformatics: An Overview of the Human Brain Project. Lawrence Erlbaum Associates, Mahwah, NJ, 1997.

    Google Scholar 

  9. De Schutter E., Bower JM. An active membrane model of the cerebellar Purkinje cell I. Simulation of current clamps in slice. J Neurophysiol 1994; 71: 375–400.

    PubMed  Google Scholar 

  10. Segev I, Fleshman JW, Burke RE. Compartmental models of complex neurons. In: Methods in Neuronal Modeling, Ch. 3. ( Koch C, Segev I., eds.) MIT Press, Cambridge, MA, 1989, pp. 63–96.

    Google Scholar 

  11. Wilson M., Bower, JM. Cortical oscillations and temporal interactions in a computer simulation of piriform cortex. J Neurophysiol 1992; 67: 981–995.

    PubMed  CAS  Google Scholar 

  12. Bhalla US, Bower JM. Exploring parameter space in detailed single neuron models: simulations of the mitral and granule cells of the olfactory bulb. J Neurophysiol 1993; 69: 1948–1965.

    PubMed  CAS  Google Scholar 

  13. Segev I. Single neurone models: oversimple, complex and reduced. Trends Neurosci 1992; 15: 414–421.

    Article  PubMed  CAS  Google Scholar 

  14. Johnston D, Magee JC, Colbert CM, Cristie BR. Active properties of neuronal dendrites. Ann Rev. Neurosci 1996; 19: 165–186.

    Article  PubMed  CAS  Google Scholar 

  15. Stuart G, Spruston N, Sakmann B, Hausser M. Action potential initiation and backpropagation in neurons of the mammalian CNS. Trends Neurosci 1997; 20: 125–131.

    Article  PubMed  CAS  Google Scholar 

  16. Vetter P, Roth A, Hausser M. Propagation of action potentials in dendrites depends on dendritic morphology. J Neurophysiol 2001; 85: 926–937.

    PubMed  CAS  Google Scholar 

  17. Rapp M, Yarom Y, Segev I. The impact of parallel fiber background activity on the cable properties of cerebellar Purkinje cells. Neural Comput 1992; 4: 518–533.

    Article  Google Scholar 

  18. Rapp M, Segev I, Yarom Y. Physiology, morphology and detailed passive models of cerebellar Purkinje cells. J Physiol (Lond) 1994; 474: 87–99.

    Google Scholar 

  19. Jaslove SW. The integrative properties of spiny distal dendrites. Neuroscience 1992; 47: 495–519.

    Article  PubMed  CAS  Google Scholar 

  20. Howell FW, Dyrhfjeld-Johnsen J, Maex R, Goddard N, De Schutter E. A large scale model of the cerebellar cortex using PGENESIS. Neurocomputing 2000; 32: 1041–1036.

    Article  Google Scholar 

  21. Ascoli GA, Krichmar JL. L-Neuron: a modeling tool for the efficient generation and parsimonious description of dendritic morphology. Neurocomputing 2000; 32: 1003–1011.

    Article  Google Scholar 

  22. Vinoski S. CORBA: integrating diverse applications within distributed heterogeneous environments. IEEE Communications Magazine, 1997, pp. 46–55. Specification available at http://www.omg.org.

  23. Hucka M, Finney A, Sauro H, Bolouri H., Doyle J, Kitano H. The ERATO Systems Biology Workbench. In: Foundations of Systems Biology ( Kitano H, ed.) MIT Press, Cambridge, MA, 2001.

    Google Scholar 

  24. a. Systems Biology Workbench Development Group Homepage http://www.cds.caltech.edu/erato, 2001.

  25. Goddard N, Hucka M, Howell F, Cornelis H, Shankar K, Beeman D. Towards NeuroML: model description methods for collaborative modelling in neuroscience. Philos Trans R Soc Lond B 2001; 356: 1209–1228.

    Article  CAS  Google Scholar 

  26. Gardner D, Knuth KH, Abato M, et al. Common data model for neuroscience data and data model interchange. J Am Med Inform Assoc 2001; 8: 17–33.

    Article  PubMed  CAS  Google Scholar 

  27. Lamport L. LaTeX: A Document Preparation System. Addison-Wesley, Reading, MA, 1994.

    Google Scholar 

  28. Biron PV, Malhotra A. XML Schema part 2: datatypes. W3C Working Draft at http://www.w3.org/TR/xmischema-2. 2000.

  29. Fallside DC. XML Schema part 0: primer. http://www.w3.org/TR/xmischema0. 2000.

  30. Thompson HS, Beech D, Maloney M, Mendelsohn N. XML Schema part 1: structures. W3C Working Draft at http://www.w3.org/TR/xmischema-1. 2000.

  31. ANSI/NISO Z39.50–1992 American national standard information retrieval application service definition and protocol specification for open systems interconnection. NISO Press, Bethesda, MD, 1992.

    Google Scholar 

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Hucka, M., Shankar, K., Beeman, D., Bower, J.M. (2002). The Modeler’s Workspace. In: Ascoli, G.A. (eds) Computational Neuroanatomy. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-59259-275-3_5

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  • DOI: https://doi.org/10.1007/978-1-59259-275-3_5

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61737-297-1

  • Online ISBN: 978-1-59259-275-3

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