Chris Gorgolewski: Multiple Comparisons

There are many fascinating and exciting developments in human cognitive and clinical neurosciences. We are constantly drawn to novel and groundbreaking discoveries. There is nothing wrong with this - I would even say that's part of the human nature. This kind of research is not, however, what I want to talk about today. This post is dedicated to people building tools that play a crucial role as a backbone of research - helping novel discoveries happen. They go beyond providing a proof of concept, publishing a paper and pointing to undocumented piece of code that works only in their labs. They provide maintenance, respond to user needs, and constantly update their tools fixing bugs and adding features. Here I will highlight two tools which in my personal (and very biased) opinion play an important role in supporting human neuroscience, and could do with some more appreciation. Early years of Captain Neuroimaging nibabel Anyone dealing with MRI data in Python must know about...

Recently my computer has been acting up. Software started crashing, compilations failing, etc. Many small errors that I could not replicate. I wasn't too concerned, because I'm a natural tinkerer - I play with software, install many different additions and one of the side effects can be an unstable operating system. Eventually my system stopped booting - the partition table was corrupted. I had to wipe it and reinstall (which was a massive pain in the ass). I also tried to run some hardware checks just in case (the computer is over three years old), but the "Apple Hardware Test" was hanging each time I run (bad sign huh?). I'v eventually run memtest86 overnight and discovered that part of my RAM is corrupted. My computer is a Mac Book Pro Retina with expired warranty. Normally I would buy new ram and install it myself, but the retina MBPs have RAM permanently soldered to the logic board. Instead of paying through the nose to get it fixed I researched softw...

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.

At a recent meeting at Leiden we talked about many issues related to data sharing. Previously I've been covering how to incentivise scientists to share data through data papers on this blog , but during that meeting we also discussed ethical issues. When we are collecting data about our participants (whether those are behavioural measures or MRI scans) we take responsibility for it. We make a pledge that we will make whatever we can to protect the identity of our subjects. This is easier if we do not share data. Because fewer people have access to the data the likelihood of someone finding a method to connects brain scans to a particular person are lower. In reality this could be done either through a security breach (someone hacking the university network and obtaining the list of participants and their anonymous IDs) or by combining multiple datasets about one person to obtain enough details to be able to identify a person (this however applies only to participants taking part ...

Beginning from 1st of March all papers published in journals run by  +Public Library of Science (PLoS)  will have to publicly share data . This includes PLoS ONE -  currently the biggest (in terms of volume) academic journal in the world. But is it a big deal? Many leading journal such as Nature , Science , and PNAS for a long time have been requiring their authors to provide data to fellow scientists upon request. Is there a difference between depositing data in a public repository and making it available upon individual requests? Yes there is. There are dozens of excuses researchers can use to delay sharing of the data almost infinitely. Additionally without proper description (which public repositories will enforce) data is useless. I could go on and on how imperfect the "available upon request" solution is, but this video depicts it in a much better way:  Making data available upon request looks good only on paper, but it just does not work in practice. Pu...

On a very cold afternoon in Berlin I managed to ask a few questions to Andrew Preston (co-founder of Publons ) who was in town for the Academic Publishing Europe 2014 conference: - Could you tell us a bit more about the platform you are building - publons.com. Where the idea came from? What kind of problems are you trying to solve? - Absolutely! I did a PhD in physics as well as a postdoc in the US, so I have experience the enjoyment and the trial of publishing papers first hand and I also have been a reviewer. By going through that process as well as talking to colleagues I realized that there must be a better way of doing this. That is the genesis of Publons. - What actually is a Publon? Good question! It is a joke in physics where there is a concept of fundamental particles: the electron is the fundamental unit of charge, the photon is the quantum of light etc. The Publon is the facetious term we use to refer to the minimum publishable unit of academic research. We thought...