Neurovault: a must-use tool for every neuroimaging paper!

Something that has long irked me about cognitive neuroscience is the way we share our data. I still remember the very first time I opened a brain imaging paper and was struck dumbfounded by the practice of listing activation results in endless p-value tables and selective 2D snapshots. How could anyone make sense of data this way? Now having several years experience creating such papers, I am only more dumbfounded that we continue to present our data in this way. What purpose can be served by taking a beautiful 3-dimensional result and filtering it through an awkward foci ‘photoshoot’? While there are some standards you can use to improve the 2D presentation of 3D brain maps, for example showing only peak activation and including glass-brains, this is an imperfect solution – ultimately the best way to assess the topology of a result is by directly examining the full 3D result.

Just imagine how improved every fMRI paper would be, if instead of a 20+ row table and selective snapshot, results were displayed in a simple 3D viewing widget right in the paper? Readers could assess the underlying effects at whatever statistical threshold they feel is most appropriate, and PDF versions could be printed at a particular coordinate and threshold specified by the author. Reviewers and readers alike could get a much fuller idea of the data, and meta-analysis would be vastly improved by the extensive uploading of well-categorized contrast images. More-over, all this can be easily achieved while excluding worries about privacy and intellectual property, using only group-level contrast images, which are inherently without identifying features and contain only those effects included in the published manuscript!

Now imagine my surprise when I learned that thanks to Chris Gorgolewksi and colleagues, all of this is already possible! Chris pioneered the development of neurovault.org, an extremely easy to use data sharing site backed by the International Neuroinformatics Coordinating Facility. To use it, researchers simply need to create a new ‘collection’ for their study and then upload whatever images they like. Within about 15 minutes I was able to upload both the T- and contrast-images from my group level analysis, complete with as little or as much meta-data as I felt like including. Collections can be easily linked to paper DOIs and marked as in-review, published, etc. Collections and entries can be edited or added to at any time, and the facilities allow quick documentation of imaging data at any desired level, from entire raw imaging datasets to condition-specific group contrast images. Better still, neurovault seamlessly displays these images on a 3D MNI standard brain with flexible options for thresholding, and through a hookup to neurosynth.org can even seamlessly find meta-analytic feature loadings for your images! Check out these t-map display and feature loadings for the stimulus intensity contrast for my upcoming somatosensory oddball paper, which correctly identified the modality of stimulation!

T-map in the neurovault viewer.
T-map in the neurovault viewer.
Decoded features for my contrast image.
Decoded features for my contrast image, with accurate detection of stimulation modality!

Neurovault.org doesn’t yet support embedding the viewer, but it is easy to imagine that with collaboration from publishers, future versions could be embedded directly within HTML full-text for imaging papers. For now, the site provides the perfect solution for researchers looking to make their data available to others and to more fully present their results, simply by providing supplementary links either to the neurovault collection or directly to individual viewer results. This is a tool that everyone in cognitive neuroscience should be using – I fully intend to do so in all future papers!

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