If you’ve visited the Neurosynth website lately, you may have noticed that it looks… the same way it’s always looked. It hasn’t really changed in the last ~20 months, despite the vague promise on the front page that in the next few months, we’re going to do X, Y, Z to improve the functionality. The lack of updates is not by design; it’s because until recently I didn’t have much time to work on Neurosynth. Now that much of my time is committed to the project, things are moving ahead pretty nicely, though the changes behind the scenes aren’t reflected in any user-end improvements yet.
The github repo is now regularly updated and even gets the occasional contribution from someone other than myself; I expect that to ramp up considerably in the coming months. You can already use the code to run your own automated meta-analyses fairly easily; e.g., with everything set up right (follow the Readme and examples in the repo), the following lines of code:
dataset = cPickle.load(open('dataset.pkl', 'rb')) studies = get_ids_by_expression("memory* &~ ("wm|working|episod*"), threshold=0.001) ma = meta.MetaAnalysis(dataset, studies) ma.save_results('memory')
…will perform an automated meta-analysis of all studies in the Neurosynth database that use the term ‘memory’ at a frequency of 1 in 1,000 words or greater, but don’t use the terms wm or working, or words that start with ‘episod’ (e.g., episodic). You can perform queries that nest to arbitrary depths, so it’s a pretty powerful engine for quickly generating customized meta-analyses, subject to all of the usual caveats surrounding Neurosynth (i.e., that the underlying data are very noisy, that terms aren’t mental states, etc.).
Anyway, with the core tools coming along, I’ve started to turn back to other elements of the project, starting with the image viewer. Yesterday I pushed the first commit of a new version of the viewer that’s currently on the Neurosynth website. In the next few weeks, this new version will be replacing the current version of the viewer, along with a bunch of other changes to the website.
A live demo of the new viewer is available here. It’s not much to look at right now, but behind the scenes, it’s actually a huge improvement on the old viewer in a number of ways:
- The viewer now handles multiple layers simultaneously, with the ability to hide and show layers, reorder them by dragging, vary the transparency, assign different color palettes, etc. These features have been staples of offline viewers pretty much since the prehistoric beginnings of fMRI time, but they aren’t available in the current Neurosynth viewer or most other online viewers I’m aware of, so this is a nice addition.
- The architecture is modular, so that it should be quite easy in future to drop in other alternative views onto the data without having to muck about with the app logic. E.g., adding a 3D WebGL-based view to complement the current 2D slice-based HTML5 canvas approach is on the near-term agenda.
- The resolution of the viewer is now higher–up from 4 mm to 2 mm (which is the most common native resolution used in packages like SPM and FSL). The original motivation for downsampling to 4 mm in the prior viewer was to keep filesize to a minimum and speed up the initial loading of images. But at some point I realized, hey, we’re living in the 21st century; people have fast internet connections now. So now the files are all in 2 mm resolution, which has the unpleasant effect of increasing file sizes by a factor of about 8, but also has the pleasant effect of making it so that you can actually tell what the hell you’re looking at.
viewer = Viewer.get('#layer_list', '.layer_settings') viewer.addView('#view_axial', 2); viewer.addView('#view_coronal', 1); viewer.addView('#view_sagittal', 0); viewer.addSlider('opacity', '.slider#opacity', 'horizontal', 'false', 0, 1, 1, 0.05); viewer.addSlider('pos-threshold', '.slider#pos-threshold', 'horizontal', 'false', 0, 1, 0, 0.01); viewer.addSlider('neg-threshold', '.slider#neg-threshold', 'horizontal', 'false', 0, 1, 0, 0.01); viewer.addColorSelect('#color_palette'); viewer.addDataField('voxelValue', '#data_current_value') viewer.addDataField('currentCoords', '#data_current_coords') viewer.loadImageFromJSON('data/MNI152.json', 'MNI152 2mm', 'gray') viewer.loadImageFromJSON('data/emotion_meta.json', 'emotion meta-analysis', 'bright lights') viewer.loadImageFromJSON('data/language_meta.json', 'language meta-analysis', 'hot and cold') viewer.paint()
Well, okay, there are some other dependencies and styling stuff you’re not seeing. But all of that stuff is included in the example folder here. And of course, you can modify any of the HTML/CSS you see in the example; the whole point is that you can now easily style the viewer however you want it, without having to worry about any of the app logic.
What’s also nice about this is that you can easily pick and choose which of the viewer’s features you want to include in your page; nothing will (or at least, should) break no matter what you do. So, for example, you could decide you only want to display a single view showing only axial slices; or to allow users to manipulate the threshold of layers but not their opacity; or to show the current position of the crosshairs but not the corresponding voxel value; and so on. All you have to do is include or exclude the various addSlider() and addData() lines you see above.