Last month we had a workshop at the University of Washington in Seattle; we focused on functional connectivity with the CONN toolbox, and different types of machine learning with The Decoding Toolbox, along with how to avoid pitfalls with using these packages. You can find the details here.
Looking forward, once I finish teaching for the semester here at the University of Michigan, in May I will be traveling to the University of Florida to give a workshop on AFNI, along with a special session about how to analyze animal brains in particular, and then shortly after that I will be hosting a workshop at the University of Wisconsin-Milwaukee on machine learning. In the latter workshop, I hope to have a working demonstration of hyperalignment, a new iteration of multi-voxel pattern analysis out of Jim Haxby’s lab, which transforms voxel-level data to a higher-dimension abstract information space, which can markedly improve classification accuracy. These are still under construction, but check the Workshops page for updates. And if you would like to have me host a workshop at your institution, and, more importantly, become part of the hall of fame, please feel free to get in touch.
Other Updates
In other news, I am updating the MRtrix walkthrough on the e-book to include Fixel-Based Analysis, which generates whole-brain maps of fixel-based values such as Fiber Density and Fiber Cross-Sections; this chapter, which is still in progress, can be found here. These maps are similar to TBSS’s diffusion tensor metrics, but unlike tensors, they are able to deal with crossing fibers. And, since I believe that MRtrix is becoming more widespread and will eventually surpass TBSS in popularity, graduate students should learn how to use it in order to stay current with the most recent methods.
I am also working with one of our tech specialists here at the University of Michigan, Bennet Fauber, to create a walkthrough about how to use the Great Lakes supercomputing cluster here at Michigan. This is an especially important skill for graduate students and all researchers to learn; if you are analyzing larger datasets, you may need to use a computing cluster to finish the analyses in a reasonable amount of time, and to store some of the intermediate results. Bennet’s tutorial sketches can be found here, and they will continue to be updated in the coming months.
While the e-book is still being regularly updated, I will include more informal updates here on the blog as well - what is in the works, where I am traveling, Novak Djokovic’s progress, and so on. More to come soon.