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Showing posts from 2015

Highlights from the NeuroImage Data Sharing Issue

This week the first part of NeuroImage special issue on Data Sharing was published. It's a great achievement and I am glad to see that more focus is being put on sharing data in our field. However the issue is a mixed bag of papers that describe different types of resources. Some of my friends were confused by this heterogeneity, so I decided to highlight some of the resources presented in the issue. The issue included papers about many data sharing platforms/databases (XNAT Central, LORIS, NIDB, LONI IDA, COINS, UMCD and NeuroVault) that are well known and covered by previous publications. Similarly some datasets (FBIRN and CBFBIRN) also have been previously covered in the literature. I understand that those have been included in the issue for completeness, but I will leave them out in this review. The original art used in the NeuroImage cover. Developmental and aging datasets The issue includes an impressive developmental dataset consisting of 9498 subjects with med

The unsung heroes of neuroinformatics

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

Software workaround for corrupted RAM in OS X

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