Using the Connectome
While the HCP data set will be an invaluable resource, many researchers will want to be able to download this data and use Connectome tools to compare it with their own data. To support these users, we are developing a set of Connectome software that will fully support browsing, download, exploration and analysis of HCP data. Connectome software will be downloadable as individual components with full documentation on installing and using the tools.
Two key tools are being developed by the Human Connectome Project consortium, as a part of our HCP Informatics Infrastructure:
- All data collected in the Human Connectome Project will be published via ConnectomeDB, a web application that will enable users to query, filter and download data, and execute Connectome processing and analysis pipelines.
- Data can be exported from ConnectomeDB and imported seamlessly into Connectome Workbench, which will be used to visualize and analyze connectivity data on population-averaged brain atlases, on surfaces and in volumes.
Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. Users will be able to connect their Connectome Workbench to these alternative ConnectomeDB instances to interact with their data.
The Connectome toolbox also includes analysis tools such as:
- FSL is a comprehensive (structural, functional and diffusion) neuroimaging software platform. FSL tools will be used in a variety of contexts in the HCP, including preprocessing, diffusion analysis and tractography, R-fMRI ICA, and parcellation.
- Brain Connectivity Toolbox (BCT) provides an access to a large selection of complex network measures in Matlab. Such measures aim to characterize brain connectivity by neurobiologically meaningful statistics, and are increasingly used in the description of structural and functional connectivity datasets
- Fieldtrip is an open source Matlab toolbox for MEG, EEG and LFP analysis. It includes algorithms for simple and advanced analysis of electrophysiological data, such as time-locked averaging, time-frequency analysis, source reconstruction using dipoles, distributed sources and beamformers, channel and source-level synchronization estimates and non-parametric statistical testing. (Related: FieldTrip Workshop webex presentation)