Learning about Clinical Brain Imaging using R at SAMSI’s Computational Neuroscience Workshop

The following was written by Katy Wang, attendee from the University of California, Riverside, of the Undergraduate Workshop focusing on Computational Neuroscience.

Dr. Ciprian Crainceanu

Dr. Ciprian Crainiceanu.

Of the seven presentations at SAMSI’s Computational Neuroscience Workshop from October 19-20th, the one that was most memorable to me was given by Dr. Ciprian Crainiceanu, a professor in the Department of Biostatistics at Johns Hopkins University. Dr. Crainiceanu’s presentation on neurohacking in R really stood out to me because I learned how to preprocess images, read, write, plot, and manipulate neuroimaging data in R.

You may be wondering “what exactly is neurohacking and how is the application of statistics used in clinical brain imaging?” As defined by Dr. Crainiceanu, “neurohacking is the continuous process of using, improving, and designing the simplest open source scripted software that depends on the minimum number of software platforms and is dedicated to improving the correctness, reproducibility, and speed of neuroimage data analysis.” The goal of neurohacking is the “democratization of neuroimaging data analysis,” in other words, to make neuroimaging data analysis possible for all people to understand. Throughout the presentation, we were shown an image of an axial slice of the T1-w image of the brain that contained a multiple sclerosis lesion surrounded by a hyper intense ring, which indicated blood with a higher concentration of gadolinium chelate. After taking the region of interest, a matrix is used with numbers corresponding to that particular section of the brain in order to understand what the dynamics of blood flow are into the lesion. To see if anything has changed (e.g, Did the brain tumor get bigger? Was the cancer eliminated by surgery?), the follow-up T1-w is subtracted from a baseline T1-w volume. A template-based analysis is also used in which an MNI T1 template is used to see which parts of the brain it maps to. The results are later quantified and mapped to neuroimage.

Students interacting with the lecturer

Students interacting with the lecturer.

Although there was not enough time to actually work with the data during the presentation, Dr. Crainiceanu offered a clear explanation on neuroimaging, an impressive tutorial with Powerpoint slides on how to set up the data, information on data structure and operations (working with various file types, visualization and data manipulation) preprocessing (inhomogeneity correction, intensity normalization, tools in R), registration, segmentation, dynamic visualization in R, and many resources in order to work with and become more familiar with working with the data. Furthermore, we were given suggested prerequisites and coursework, such as (1) Linux/Unix; (2) a basic knowledge of programming; (3) a basic knowledge of array data structures (e.g. 2d and 3d arrays), and most importantly (4) an interest in “hacking” with neuroimaging data! You may also find these Coursera Data Science Specialization courses offered on behalf of Johns Hopkins University as a helpful resource.

All in all, SAMSI’s undergraduate workshop was truly a great learning experience! I went into the workshop with very limited knowledge in computational neuroscience but came out of the workshop with several Word documents of notes, many data files/tutorials, and resources to enhance my knowledge of mathematical and statistical methods in neuroscience.

Advertisements

Predicting number of landfalls of hurricanes — Undergraduate Modeling Workshop produces forecasts for 2013

group shot of undergraduates attending May 2013 workshop

Undergraduate workshop from May 2013.

Thirty-four undergraduate students from around the U.S. came to SAMSI and NC State University the week of May 13-17. During the week, the students interacted with an atmospheric scientist who works on hurricane research, and applied mathematicians and statisticians who work on climate research.  Students used the same database as used at NCSU to forecast various aspects of future hurricane seasons, and built Poisson regression models within R to produce their own forecasts of the 2013 hurricane season in the US. Below are some comments from participants:

three students with signs

Corey Raphael, U. Florida, Jonathan Skantz, U. Florida and Gwen Tian, U. British Columbia.

Corey Raphael, University of Florida
“I had a great time during my week at SAMSI! I learned all about climate science and hurricane predictions, and met a lot of great people. Thanks for all the advice and free food! I enjoyed getting to know the Raleigh area, and I learned a lot about R that I didn’t know previously. I hope the program enjoyed having me as much as I enjoyed being here!”

Group 3 shot

Evan Bittner, Penn State, Kasey Palmquist, UNC Wilmington, and Daria Drozdova, Pomona College.

Kasey Palmquist, University of North Carolina at Wilmington
“The workshop was an excellent experience; I truly feel that I am not leaving empty-handed. I not only learned new methods of statistical analysis, but how to collaborate with a group of people on a research topic. I found this workshop beneficial because it allows undergraduates to get a “feel” of mathematical/statistical research in order to see if it is right for them. I found the workshop to also be a great way to network and meet people that share the same interests as you. Overall, great experience!”

Group 6 SAMSI undergraduate modeling workshop May 2013

Brandon Sherman, U. Pitt, Kehao Zhu, Purdue, and Vinicius Taguchi, NCSU

Vinicius Taguchi, North Carolina State University
“This workshop was a wonderful experience.  I gained a better appreciation for statistics and applied mathematics, made lasting friendships, and got to see a new side of NC State University.  When I first got here, I was a little concerned about being one of the few non-math/stats majors, as well as one of the very few underclassmen.  Nevertheless, this never became an issue and I felt like part of the group right from the get-go.  Thank you, SAMSI.”

Group 2 photo SAMSI undergraduate modeling workshop May 2013

Lee Richardson, U. Washington-Seattle, Charles Ho, Rice and Anna Peris, Marquette.

Lee Richardson, University of Washington at Seattle
From his Twitter feed – “Predicted a Poisson Distribution with a mean 3.96. AKA 56% chance of greater than 4 hurricanes!!!!!”

Here are some of the presentations that the students gave the last day of the workshop.

Impressions from the Undergraduate Workshop on Data-Driven Decisions in Healthcare

big group of students outside SAMSI

February 2013 Undergraduate Workshop participants.

SAMSI recently held the Undergraduate Workshop on Data-Driven Decisions in Healthcare for about 30 students. Visiting professors, postdoctoral fellows and graduate fellows who are participating in this SAMSI program led the sessions providing cutting-edge research into the lectures. Students had a chance to work with data from the SEElab at Technion in Israel, got an overview of personalized medicine and a tutorial in R and a demonstration of the ARENA software.  Here are a few of the students’ impressions from the workshop.

Eric Laber instructing students

Eric Laber, NCSU, giving lecture at the workshop.

Eric Kernfeld, Tufts University Class of 2014, Applied Mathematics

“I had a great time at the workshop on Data Driven Decisions in Health Care this past weekend. It was a nice opportunity to meet statisticians, something I don’t get the chance to do back at Tufts. I also met a lot of undergraduates majoring in statistics and mathematics. The food was good, the staff were welcoming, the accommodations were convenient, and the talks were well-pitched. I recommend SAMSI workshops to anyone who’s interested in the topics, especially to people considering graduate education down the road.”

Danielle Llanos, Georgetown University

“I thought the SAMSI workshop was wonderful. It was a great opportunity to learn from talented individuals, and a chance to expand my network. The lecture topics were incredibly interesting and were very relevant to my career goals. Probably the best part of the workshop was the graduate student panel. The ability to ask those burning questions and learn from the experiences of others was great. I would recommend any SAMSI workshop to students looking to learn more about opportunities in the sciences, and expanding their educational experiences.”

three students at table

Students networking at lunch.

Brittany Boribong, sophomore, biomathematics major at University of Scranton

“As a student with no background in statistics and programming, I found the workshop a bit overwhelming but no less interesting. Coming into this with no experience just allowed me to take that much more out of the workshop.  I was able to explore new fields of math that I never considered before and learn about topics that I had no idea even existed. As a Biomathematics major, I found the topic of using data to derive decisions in healthcare intriguing since it is an application of my major that I was not aware of. Another wonderful aspect of the workshop was the chance to speak to people in different fields. During lunch, I had the opportunity to speak to a post-doc fellow and during dinner, I spoke to one of the professors that gave a lecture earlier in the day; these opportunities don’t come along every day. It was enjoyable hearing their stories and being able to have a casual conversation with them. The panel made up of current graduate students and post-docs was also helpful in that they were able to share their experiences about graduate school and offer along any advice. I found it particularly helpful since one of the speakers was currently in a biomathematics program and I was able to ask questions I had about my major.

However, the best part of the workshop, in my opinion, was being to meet other students. Coming from a university with a smaller math department, I really enjoyed meeting students from around the country with interests similar to my own. It was great being able to make connections with students in different fields and from universities from all over. Overall, I had a wonderful time meeting new people and exploring different fields of mathematics during the workshop and found this to be a great experience.”