The Connectome Viewer Toolkit: An open source framework to manage, analyze, and visualize connectomes
- 1 Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- 2 Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit – a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer’s plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/
Keywords: connectomics, connectome, neuroimaging, python, multi-modal data, data management, network analysis, visualization
Citation: Gerhard S, Daducci A, Lemkaddem A, Meuli R, Thiran J-P and Hagmann P (2011) The Connectome Viewer Toolkit: An open source framework to manage, analyze, and visualize connectomes. Front. Neuroinform. 5:3. doi: 10.3389/fninf.2011.00003
Received: 28 February 2011;
Accepted: 18 May 2011;
Published online: 06 June 2011.
Reviewed by:
Dennis Säring, University Medical Center Hamburg-Eppendorf, Germany
Daniel Marcus, Washington University in St. Louis, USA
Copyright: © 2011 Gerhard, Daducci, Lemkaddem, Meuli, Thiran and Hagmann. This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.
*Correspondence: Stephan Gerhard, Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne – STI-IEL-LTS5, CH-1015 Lausanne, Switzerland. e-mail: stephan.gerhard@epfl.ch