Software
We would like to build up this list of software packages, so if your group in Switzerland has developed (or part-developed) some Open Source software useful for neuroinformaticians, especially in the field of neural reconstruction, please let me know: mailto:longair@ini.phys.ethz.ch
CX3D
CX3D is a Java package for the simulation of the development of neural tissues. It allows cell division, migration, extension of neurites to form axonal and dendritic arbors, synapse formation, and the production and detection of signaling molecules.
Beside the implementation of these biological processes, CX3D also takes into account the physical properties and interactions of the cells: neurons are decomposed into discrete elements, each one with a volume, an elasticity and a friction coefficient to simulate the mechanics of the cells. The program also allows diffusion of chemicals both in the extra-cellular matrix and inside the cells.
This figure, taken from Frédéric Zubler's PhD thesis, shows the results of a cortical development simulation. In a laminated structure representing the cortical layers, various cells extend axons and dendrites, reproducing the typical branching patterns of five different types of cortical neurons. From left to right: a layer 2/3 pyramidal cell; a layer 4 spiny stellate cell; a layer 5 pyramidal cell; a layer 6 pyramidal cell; and a layer 2/3 basket cell. The top row shows the individual cells; the bottom row shows the cells in the context of the cortical layers.
Many videos showing CX3D can be found via this YouTube channel.
Connectome Viewer
The Connectome Viewer application was developed to meet the needs of basic and clinical neuroscientists, as well as complex network scientists, providing an integrative, extensible platform to visualize and analyze Connectomics data.
The Connectome Viewer was developed by by Stephan Gerhard, supported by Patric Hagmann (UNIL-CHUV), Jean-Philippe Thiran (EPFL / LTS5), Reto Meuli (UNIL-CHUV) . The development of the tools is funded by the Ecole Polytechnique Fédérale de Lausanne (EPFL) and the Hospital Center and University of Lausanne (UNIL-CHUV), Switzerland.
Diffusion Spectrum Imaging data has been processed by the Connectome Mapping Pipeline, bundling white matter tracts and producing networks in multiple resolutions (number of nodes) and with different edge attributes. The image was rendered using the ConnectomeViewer application. This network has 258 nodes corresponding to cortical and subcortical ROIs (shown as blue cubes and as transparent surfaces), the edges depict threshold and color-coded densities between connecting ROIs.
For use cases showing what can be done with Connectome Viewer, see these screencasts.
A related project is the Connectome Wiki, which enables the retrieval of additional literature and knowledge about mesoscale brain regions (nodes) and connections (edges) for appropriately linked connectome data in the Connectome Viewer.
CATMAID
CATMAID is a project now under active development by the INCF Swiss Node to provide a web-based interface for live, multi-user annotation of very large data sets, such as those generated with SBFSEM or ssTEM. We are working on extending the annotation system to provide a richer, structured set of annotation types. CATMAID was developed by Stephan Saalfeld, Albert Cardona, Volker Hartenstein and Pavel Tomančák and is currently being further developed by Stephan Gerhard and Stephan Saalfeld.
TrakEM2
TrakEM2 is an ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation. It was designed by Albert Cardona and Rodney Douglas at INI, Zürich, is implemented and developed by Albert Cardona, Stephan Saalfeld and others and is distributed as part of Fiji. TrakEM2 is particularly suited for the task of annotating large electron microscope image data sets.
For examples of what can be done with TrakEM2, see these screenshots and descriptions.
Fiji
Fiji is an easily installable distribution of ImageJ bundled with many useful plugins for biomedical image processing. Fiji is used by many groups in Switzerland for visualization, annotation and analysis of neuroscientific image data. Almost all components in Fiji are released under Open Source licenses, which makes it an excellent platform for developing rich applications (such as TrakEM2 above). There is extensive documentation available for Fiji on the wiki, and the source code can be obtained as described here.
