The field of Connectomics research benefits from recent advances in structural neuroimaging technologies on all spatial scales. The need for software tools to visualize and analyse the emerging data is urgent.
Python is emerging as standard programming language in neuroscience/neuroinformatics. Thus it makes sense to build a reusable application using Python for Connectomics research, allowing the use of many scientific tools.
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.
With the Connectome File Format, interlinking different datatypes such as networks, surface data, and volumetric data is easy and might provide new ways of analyzing and interacting with data.
Beginning 2009, Stephan Gerhard, master student at the Institute of Neuroinformatics, was looking for an interesting subject for his thesis.
Fascinated by an image on VisualComplexity.com of recent advances in structural in-vivo neuroimaging in humans led him to find out about the Human Connectome project in a paper by Olaf Sporns and Rolf Kötter. (Publications)
Bringing computer science and neuroinformatics know-how into this surely long-lasting endeavour seemed like a good way to go. After contacting Dr. Olaf Sporns, he pointed him to a collaborating signal processing group at EPFL in Lausanne.
Prof. Jean-Philippe Thiran, the head of the LTS5 group, allowed him to start his master thesis supervised by Dr. Patric Hagmann, a Diffusion Spectrum Imaging specialist.
In February 2010, the master thesis (Publications) was finished. The development of the Connectome Viewer will be continued at EPFL and UNIL-CHUV by Stephan Gerhard et al.