Content of review 1, reviewed on October 22, 2014

Gorgolewski and colleagues here officially introduce and principle-of-proof check a new kind of neuroimaging platform called NeuroVault. This is a web-provided service to upload and share different types of 3D nifti volumes. This is not limited to volumes of Z/T values from fMRI and PET analyses, but includes also VBM, diffusion MRI, as well as source-reconstructed EEG/MEG data. In comparison to conventional nifti-data-sharing websites, one might want to stress the explicit support for sharing ROI (region of interest) maps, maps from neurological lesion studies, label maps (e.g., from connectivity-based parcellation investigations), and posterior probability maps (from Bayesian statistics). This might help to leverage Open Data by operation-system-independent sharing via a web-interface used by researchers in neuroscience. More generally, such approach could improve the outreach to an interested public.

However, NeuroVault attemps to go beyond simply making data accessible. This is enabled by its seamless integration into a vibrant Open Source ecosystem, including for instance Papaya (Research Imaging Institute, San Antonio, USA), Neurosynth (Tal Yarkoni), and pycortex (Gallant lab, Berkeley, USA). An identical dataset can thus be viewed at different threshold options, rendered onto different brain templates, and personalized by different cosmetics. The maps can also be submitted to automatic functional decoding by assignment to cognitive principles. It is an intriguing possibility that future neuroimaging paper publications might be complemented by links to such interactive access to the discussed results. Further, it might be an ideal platform for quantitative cross-study comparison and synthesis. Even more so, the bundled access to results from diverging imaging techniques will be important for future large-scale projects of cross-modality fusion. The accumulation of neuroscientific finding is helped by the possible extension to novel types of machine-readable meta-data. The only downside I see is the currently missing integration with neuroanatomy that could by realized by quantitative comparison to probabilistic cytoarchitectonic maps. More generally, NeuroVault being a social-coding project on Github might foretell a rapid evolution of this initiative.

Massive, clean, well-annotated, and easily accessible data will be a critical prerequisite for statistical learning of human functional brain architecture in health and disease. In this regard, NeuroVault has the potential to push imaging neuroscience to the next level of publication practices, inter-laboratory collaboration, as well as the structured discovery and propagation of neurobiological knowledge.

Danilo Bzdok

Source

    © 2014 the Reviewer (CC BY-SA 3.0).

References

    J., G. K., Gael, V., Gabriel, R., Yannick, S., S., G. S., Camille, M., V., S. V., E., N. T., A., P. R., Jean-Baptiste, P., Tal, Y., S., M. D. 2015. NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Frontiers in Neuroinformatics.