A realistic neuronal model represents a modeler's understanding of the structure and function of a part of the nervous system. As the number of neurobiologists constructing realistic models continues to grow, and as the models become ever more sophisticated, they collectively represent a significant accumulation of knowledge about the structural and functional organization of nervous systems. But at the same time, 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.

With support from The Human Brain Project, we began by exploring the construction of a brain database based on our existing neural simulation system, GENESIS. This was a feasibility study for a novel approach to neural database construction, organization, and interaction.

The Modeler's Workspace was originally conceived as the user interface to this system. As the design has evolved, the creation of a next-generation interface for collaborative neural simulations has become our goal. Although the initial version uses GENESIS as the simulator, the design permits the use of multiple simulation systems, with or without the use of a database. This allows modeling at multiple levels of scale from the molecular level, through the subcellular (e.g. ion channel), single cell, and network levels, to the systems level (e.g. relating models to fMRI studies).

The Modeler's Workspace is a collection of software tools that enable users to interact over the WWW with databases of models and data. It provides 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.


The Modeler's Workspace is written in Java for portability and extensibility. It is modular in design and uses pluggable components for supporting different data formats, which means that new data types can be supported by loading an appropriate plug-in. To increase the probability that the Modeler's Workspace will be compatible with future databases and tools, we are using the eXtensible Markup Language (XML) as the interchange format for communicating with databases.

One of the most difficult conceptual issues has been developing a scheme for describing models and their components. The critical issue has been balancing the need for specificity in the representation scheme (so that we can develop software to manipulate the objects) with the need for extensibility (so that as people's conceptualizations of neuronal characteristics change, the software does not need to be rewritten). We began with an extensible, object-oriented scheme developed by Gardner et al. (Soc. Neurosci. Abstr. 25: 1910), and designed containers for representing models at the single-neuron and network levels of scale. We are working on expanding this representation to span a much broader range of scales, from the molecular level to the systems level.