More than 40 neuroscientists gathered at the University of Washington eScience Institute for the first-ever Neurohackweek, held Sept. 5 – 9. Inspired by AstroHackWeek and previous brainhack.org events, the week was part conference, part summer school (including tutorials on cloud computing with Amazon Web Services, image processing with open source tools, modeling and statistics, and many others), and in large part focused on group work on novel computational projects, or “hacks” in human neuroscience.
In recent years, several data-sharing initiatives in human neuroscience have seen a tremendous growth in openly available data-sets for research. Through projects such as the Human Connectome Project, large data-bases of high quality data are increasingly becoming available. Neurohackweek attendees, including graduate students, post-docs, research staff and faculty from all over the U.S., and from the U.K. and Holland, focused on the analysis of these open data-sets and on using open-source software to implement a variety of analyses of the data.
Projects included implementations of new features within existing libraries (e.g., FeatureX, mindcontrol, and MRIConvert), novel algorithms for quality control in pediatric imaging, a new system for the analysis of cognitive ontologies called cogfusion, and even original open source software to enable 3D printing of individual brains from MRI images.
The event, co-organized by Ariel Rokem (eScience Institute) and Tal Yarkoni (UT Austin), included participation by eScience affiliates Bing Brunton and Jason Yeatman, and eScience staff members Jake Vanderplas, Valentina Staneva and Bernease Herman, who taught tutorials on machine learning, Python programming and software version control.
Guest lecturers from other institutions included Russ Poldrack and Chris Gorgolewksi from Stanford University, Kendrick Kay from the University of Minnesota, and Satra Ghosh from MIT. Terri Gilbert and Jeremy Miller, both from the Allen Institute for Brain Science, exposed the participants to the wealth of data that AIBS is making available to researchers.