Chris Gorgolewski: Multiple Comparisons

I'm often asked how to go from voxel and mm coordinates using Python. This can be easily achieved using nibabel package with only few lines of code. The following tutorial is based on +Matthew Brett   answer on the nipy mailing list . Going from voxel to mm coordinates import os import nibabel as nib Load the NIFTI file defining the space you are interested in. For the purpose of this tutorial we will use a test dataset shipped with nibabel. data_fname = os.path.join(os.path.dirname(nib.__file__), 'tests', 'data', 'example4d.nii.gz') img = nib.load(data_fname) Get the affine matrix and convert the coordinates. aff = img.get_affine() real_pt = nib.affines.apply_affine(aff, [22, 34, 12]) real_pt array([ 73.85510254, 27.1169095 , 29.79324198]) Going from mm to voxel coordinates Going the other direction is even easier. import numpy.linalg as npl nib.affines.apply_affine(npl.inv(aff), real_pt) array([ 22., 34., 12.])

We have recently added a new feature to NeuroVault - you can embed statistical maps in external websites and blogs. They look just like this one below: It's very easy to use. You just need to upload you statistical maps (unthresholded, NIFTI file format in MNI space) to NeuroVault and click on the "Embed" tab. Copy the HTML code snippet and paste it to your blog or website. This feature has been long awaited by some modern academic journals (like +F1000Research ) as well as some neuroimaging bloggers (see +Micah Allen   post about NeuroVault . It is still in beta so we would appreciate your feedback.