University of Washington Workshop Complete and Other News

April 12, 2023 Andrew Jahn

Beautiful Mt. Rainier in the distance, as seen from the University of Washington’s Red Square. Legend has it that the University’s evil capitalist overlords decided to pave this once-grassy area with bricks, which, once they became wet with Seattle’s frequent rains, would become dangerously slick and therefore discourage godless communists from protesting. Fact or fake news? Let me know if the comments down below.

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.

Updated: FreeSurfer Job Submission on Open Science Grid

February 22, 2022 Andrew Jahn

A few years ago, I created a tutorial about how to use a supercomputing cluster called the Open Science Grid. The supercomputer was available to all researchers affiliated with a United States institution, and it was easy to analyze large numbers of FreeSurfer subjects in a short period of time; for those whose analyses were restricted mostly to FreeSurfer, it was like having your own personal supercomputer. Once the data was analyzed you could then download it to your local machine and use it however you like.

In 2019 someone told me that FreeSurfer was no longer being supported on the Open Science Grid; consequently, I removed the video I had on YouTube explaining how to use it, and put a disclaimer on the corresponding chapter of Andy’s Brain Book. Recently, however, alert reader Christina Koch let me know that although fsurf has been deprecated, there is a new way to submit FreeSurfer jobs to the Open Science Grid. Here is what she wrote on my e-book:

“fsurf has been deprecated and is no longer supported; to run Freesurfer jobs on the OSG, you can request an account on the OSG Connnect service (available to all researchers affiliated with a US-based institution or project) and then follow the instructions on this page which shows how to submit your own Freesurfer workload to the OSG.”

I haven’t gotten the chance to work with it yet and make an updated video about how to use it, but I encourage everyone to check it out. If there are any issues, let me know before I begin trying it on my own.

Matlab Errors: License Manager and mexmaci64

February 16, 2022 Andrew Jahn

Working from home during a pandemic can be exhausting: Choosing what not to wear, what not to pack for lunch; one day, I hope, our descendants will look back at us and appreciate the sacrifices we made. Sure, our great-grandfathers stormed the beaches of Normandy and fought the Kaiser and all that, but they never had to deal with digital eyestrain from back-to-back Zoom meetings - sometimes more than three or four in a row. I’m not asking for a parade here; we were just doing our job.

But if that wasn’t bad enough, some of us also have problems with Matlab connecting to its license server. For those working remotely, you may have come across this particular error message when opening up Matlab:

Digital Object Identifier for Andy's Brain Book!

January 20, 2022 Andrew Jahn

For those who would like the cite the e-book (https://andysbrainbook.readthedocs.io/), you can use the following template:

"We followed the AFNI preprocessing pipeline as outlined in Andy's Brain Book (Jahn, 2022. doi:10.5281/zenodo.5879293)."

Thanks for Dan Bullock for advising me on how to do this with Zenodo, and for others who have asked for a way to cite the resource.

In addition, I have an announcement coming soon about new directions for this website and for the e-book; this will include new tutorials on software packages such as CAT12, methods such as FIR analysis and fixel-based analysis in MRtrix, and how to analyze data from large open-access repositories such as ADNI and the Human Connectome Project. Keeping current with the latest trends in neuroimaging analysis is the main goal of this blog, and I want to keep it up.

fMRI Data Analyst Position at SDSU

January 13, 2021 Andrew Jahn

The following job advertisement was sent to me by Dr. Jillian Wiggins of San Diego State University (SDSU). I’ve been to San Diego, and I have to warn you: If you don’t like beaches, the ocean, and warm, sunny weather nearly all-year round, you probably shouldn’t go. California’s public relations department has been very keen on suppressing those details.

**HIRING NOW** Data Analyst (MRI Research)

Translational Emotion Neuroscience and Development Lab

San Diego State University

Drs. Jillian Lee Wiggins (San Diego State University) and Lea Dougherty (University of Maryland College Park) and the Translational Emotion Neuroscience and Development Lab (https://tendlab.sdsu.edu/) in the Department of Psychology at San Diego State University (SDSU) in San Diego, CA is seeking to hire a full-time data analyst for an NIMH-funded research project examining neural mechanisms of mental disorders across childhood and adolescence, using functional and structural MRI methods.

The data analyst will be involved in the analysis of neuroimaging data (especially functional MRI) using standard group analysis, in addition to advanced methods including machine learning, graph theory/network analysis, and neural networks. The successful candidate will also assist with adapting fMRI paradigms and may periodically perform MRI operator duties (training in this will be provided). The data analyst will be expected to be a co-author in multiple research publications.

The ideal applicant will have a Master’s degree in Engineering/Computer Science (or related field) and experience with MRI data acquisition and analysis (AFNI, SPM, FSL, Freesurfer, etc.). Computer programming experience is necessary (Python, Matlab, R, etc.), including familiarity with Linux environments. Knowledge of statistical methods is highly desirable. Strong organization and problem-solving skills are essential, as is the ability to work independently.

Salary will be competitive, commensurate with experience, and include health benefits. The position is currently remote (teleworking) but will transition to in-person as COVID-19 restriction abate.

Interested individuals should email a cover letter, CV, and names and contact and contact information of 3 references to Jillian Lee Wiggins (jillian.wiggins@sdsu.edu) and Lea Dougherty (ldougher@umd.edu). Please include all documents in a single pdf file and include your last name in the file (i.e., “LASTNAME.pdf”). Application review will begin immediately.

SDSU is an equal opportunity affirmative action employer with a commitment to racial, cultural, and gender diversity. Women and minorities are encouraged to apply.

The Dvořák Piano Quintet: Mastery of Rhythm

December 21, 2020 Andrew Jahn

“I should be glad if something occurred to me as a main idea that occurs to Dvořák only by the way.”
-Johannes Brahms

On August 16th, 1887, Dvořák wrote to his friend Alois Göbl a letter that must have been - by Dvořák’s standards - relatively uninteresting. We can imagine that he spent time describing some of the minor details of his life at the moment, such as the weather, his health, and his finances. The Czech composer would almost certainly have let his friend know about a new composition if he had started one, often writing in excited tones about a new idea or a recently finished piece; instead, he wrote “…now I am doing nothing new…”

Introduction to Multi-Voxel Pattern Analysis with The Decoding Toolbox

December 20, 2020 Andrew Jahn

Five years ago, during the UCLA Neuroimaging Training Program, I first learned how to do multi-voxel pattern analysis, or MVPA. There were a few different tools that we could choose from, and I remember that one of them called The Decoding Toolbox seemed quick, intuitive, and easy to use. At the time I was looking for new software packages to promote, and The Decoding Toolbox seemed like an excellent candidate; too many students, myself included, would get bogged down with other packages that had a steep learning curve, seemingly unapproachable if you didn’t already have a strong background in how to do the analysis. What was needed was a “shallow ramp” for beginners; a package that could get them started, and which they could also use for more advanced analyses, too.

Fundraising Ideas

December 9, 2020 Andrew Jahn

How to make more money? Everybody has thought this at one time or another: Beethoven thought about it when he defrauded his publishers; Napoleon thought about it when he had to raise cash for his wars of conquest; and finally, academics think about it all the time when they are paid starvation wages.

Website Updates

December 4, 2020 Andrew Jahn

Although most of my time has been spent on the e-book, recently I have made a few updates to this website as well. The Research section has been removed, since that is no longer the focus of my work; a couple of new Workshops have been added; and the Publications and CV pages have been updated.

For those looking for new training walkthroughs, the Videos gallery now contains four new playlists:

Standardized Preprocessing with fMRIPrep;
Diffusion Analysis with MRtrix;
Connectivity Analysis with the CONN Toolbox; and
fMRI Analysis with SPM.

Introducing Andy's Brain Book

April 18, 2020 Andrew Jahn

Neuroimaging analysis, like sex, is a fun, exciting activity sometimes resulting in death. Although it is an enjoyable pastime for responsible adults, however, each year sees the arrival of ever-increasing numbers of inexperienced youngsters who also want to participate. Often their interest is piqued by irresponsible professors and academic rakehells extolling the pleasures of cortex, neurons, and brain science; other times, their imagination is aroused by lurid images in seedy neuroimaging journals depicting impossibly large brain activations - often, it should be added, achieved without using proper correction, correction which most researchers piously encourage in public but secretly admit dampens spontaneity and feels unnatural.