Postdoc Profile – Benjamin Risk

Ben on top of a mountain in the Galapagos

Benjamin Risk traveling in the Galapagos Islands.

As Ben Risk was growing up in Northbrook, Illinois, (a suburb of Chicago) he always liked to look out in the yard and see the birds soaring above. “As a kid, I was really interested in biology and ecology and birds,” said Ben.

He went to Dartmouth for his undergraduate work where he decided to major in environmental and evolutionary biology. He collected data on the breeding demography of a songbird called the black-throated blue warbler, which got him interested in statistics. “As an undergraduate I had to do a lot of statistical analysis and I had to get help on that because I didn’t have the training. That was the first exposure I had to the importance of statistics,” Ben commented.

Ben writing notes in a notebook on a mountain

Ben in Wrangell St. Elias National Park in Alaska.

After graduating, he moved to Oakland, California, and worked for a few years for an economic consulting firm, Charles River Associates, where he applied statistical methods to anti-trust litigation and environmental economics. “We would come up with a dollar value for how much companies had increased prices through collusion and things like that,” Ben explained, “I was following the instructions of the statisticians, and that also motivated me to consider becoming one of those statisticians.”

He then went to graduate school and received a Master’s degree in environmental science from the University of California, Berkeley. His thesis developed a Bayesian formulation of a metapopulation model. “I was realizing that by specializing in statistics I could be involved in many different fields. I also wanted to be involved in research that would have applications to human health, so I decided I wanted to pursue biostatistics research,” said Ben. It was at that point that Ben enrolled in the Ph.D. program in statistics at Cornell University.

A lot of people at Cornell have been involved with SAMSI, and Ben’s advisors, David Ruppert and David Matteson, also mentioned SAMSI as a place to apply to after he finished his degree. The program on computational challenges in cognitive neuroscience was also announced at JSM 2014, which prompted him to email Haipeng Shen.

Ben is currently researching statistical methods for the analysis of MRI. He is working on one project with Hongtu Zhu, where they are developing a spatial model of the heritability of cortical attributes that are correlated with intelligence. “We are looking at cortical thickness and volume to assess the degree of nature versus nurture,” he explained. He is also working with Daniel Rowe to examine how image processing may affect the conclusions people make regarding which parts of the brain are connected.

Ben typing in his computer on a rock in the Galapagos

Taking measurements of a tortoise in the Galapagos Islands.

Ben is involved in three working groups. He is in the Functional Imaging Methods and Functional Connectivity working group with Jon Aston and Hernando Ombao. He is in the Big Data Integration in Neuroimaging working group with Martin Lindquist and Timothy Johnson. He is also in the Acquisition, Reconstruction, and Processing of MRI Data working group with Dan Rowe.

Ben is an NIH trainee, so will continue his research at SAMSI next year. He is also associated with UNC’s biostatistics department, so will spend time there as well.

When Ben has time, he likes to go cycling and to play guitar. Of course, he still loves birds, so he also likes to go birding when he has time.

Advertisements

Taking a Different Road – Being a Statistics Major

The following is written by Sarah Lotspeich, University of Florida who attended the SAMSI Undergraduate Workshop focusing on Computational Neuroscience.

I declared my Statistics major in the eleventh grade, approximately halfway through my AP Statistics course. As everyone around me pondered medical school and the many types of engineering, I knew that my choice seemed unconventional. Now three years into my undergraduate degree, I have met only a handful of fellow Statistics majors to date. During the third week of October, however, this changed forever as I attended the SAMSI Undergraduate Workshop.

Duke Chapel

Duke Chapel.

It was a gorgeous fall day (a pleasant surprise for me, as my typical “fall” in Gainesville, Florida includes a few fallen leaves and a high temperature in the 80s) in Research Triangle Park, North Carolina. Budding statistics and mathematics students from across the country gathered to explore computational neuroscience, and to enjoy fantastic food. Always eager for an adventure, I flew in as early as possible the day before the workshop to get maximum exploring time in Durham. Perhaps a bit TOO eager, I walked over eight miles through Downtown Durham and to both edges of Duke University’s gorgeous gothic campus.

Dame's Chicken and Waffles

Excellent chicken and waffles place!

Fret not, however, as I was well fueled by Dame’s Chicken and Waffles and fondue from the Little Dipper. Needless to say the local area surpassed my every expectation and left me excited to wear scarves and learn more about statistics the following day. The mingling began at approximately 7:30am the next morning, as over thirty of my fellow “numbers people” bonded over bagels and oatmeal. I was so excited to hear from people who care as much about significance tests and p-values as I do!

The presentations commenced with an absolute bang as Dr. Ciprian Crainiceanu of Johns Hopkins University immersed us in “Neurohacking”. He outlined the basic principles of converting MRI images from picture to a system of numbers, and by the end of the hour left us with a data set and the necessary code to explore it independently. One of my favorite components of the workshop, actually, was the interactive nature of each presentation with the integration of R or Matlab code.

Guest lecturers introduced many fascinating facets of computational neuroscience, and I especially enjoyed how my knowledge on the subject compounded with each additional lecture. As the workshop progressed I found that I was relating information from one speaker’s presentation back to material I learned even hours previously, and even today I walked away with a nice basis on the topic. It very much feels as if I went from zero to one hundred with this material, and I appreciate the challenges posed to us by the complicated subject matter.

Beyond the presentations, the field trip to the laboratory for psychiatric neuroengineering at Duke University provided a “behind-the-scenes” glimpse at the processes of data collection that create the massive sets we dealt with during lecture. I was also just happy for any excuse to ogle the beautiful campus once more. Each new speaker and opportunity brought about new questions to ask and facts to learn, so I was happy for the constantly changing environment of the workshop from lecture to lecture, or even breaks for the field trip or panel.

students by SAMSI sign

From left to right: Jordan Zeldin, Eion Blanchard, Sarah Lotspeich, Michelle Zamperlini.

The many bus rides provided unexpectedly pleasant opportunities to meet new people, as well, as I was shuffled into new groups with each trip. I thoroughly enjoyed swapping stories about my university – about the weather, everyday dress code, the statistics department – with people from other schools! And I was even lucky enough to give suggestions about things to do and places to eat in Florida, as one of my new friends is planning a trip to the Sunshine State soon. Perhaps the most unexpected bonus to this experience was the people.

This was honestly one of the most incredible groups of students, and upon learning more about each person and their involvement I am absolutely honored to have been selected among them for the 2015 SAMSI Undergraduate Workshop. Though the workshop lasted only two day, the people I met and research I was immersed in will carry through my entire career. I cannot emphasize enough the importance of this experience and how strongly I recommend it.

There is a 100% probability that I would love to return to SAMSI sometime in the future.

Learning about the challenges of computational neuroscience

The following was written by Thomas Witelski, Associate Director at SAMSI and Professor at Duke University in the Mathematics Department.

At some level, everyone is aware of the pressing medical and societal
challenges of neuroscience from media coverage of the growing impact of
neurological diseases like Alzheimer’s and Parkinson’s. Understanding the
brain at a scientific level has been identified as one of the central
challenges for this century’s research, as reflected in the magnitude of
resources invested in the NIH’s BRAIN initiative and the European Union’s
Human Brain Project.

attendees sitting in the auditorium

The opening workshop for CCNS was held at the NC Biotech Center.

In August, a diverse community of researchers converged at the NC
Biotechnology Center for SAMSI’s opening workshop for the Challenges in
Computational Neuroscience (CCNS) program. The presentations by leading
researchers on clinical, cognitive, computational and theoretical aspects of
brain research yielded many very lively discussions. Some talks addressed
technical issues, but many pointed to big fundamental questions on
exploring what might be nature’s most intricate black box.

Martin Lindquist speaking at the podium

Martin Lindquist, Johns Hopkins, speaking at the opening workshop.

A long history of anatomical studies has established the general features
comprising the human brain, but great challenges lie ahead in making clear
how the structure and functions of the brain relate to each other. Many of
the talks in the CCNS workshop addressed methods in neuroimaging. Martin
Lindquist (Johns Hopkins Univ) gave a lecture over viewing the various
modalities for functional imaging of brains in vivo, including functional
magnetic resonance imaging (fMRI), positron emission tomography (PET), and
electro/magneto-encephalography (EEG/MEG). These techniques differ in the
technologies used to collect data, but more importantly, they fundamentally
differ in the physiological types of behavior they monitor — in terms of
either blood flow, metabolic activity or electrical activity in the brain.
The methods have different limitations and trades-off in terms of spatial
and temporal resolutions, and represent the current state-of-the art in
clinical methods of collecting neuroimaging data.

Several talks in the meeting addressed fundamental statistical and
mathematical questions on image processing and how to use collected data
(possibly coming from multiple scans) to obtain the most accurate possible
maps of the brain’s structure. Of particular interest is the use of
neuroimaging data to infer the networks of connections among parts of the
brain, called the field of connectomics. In this direction, Max Descoteaux
(Univ of Sherbrooke) showed how diffusion in MRI images could be used to
identify structural connections within the white matter of the brain.

Another major branch of neuroscience research explored in the workshop is
based on “bottom-up” modeling of time series of neural activity in networks
of connected neurons. Physiologically-based models of chemical/electrical
activity like the Hodgkin-Huxley equations can effectively reproduce the
dynamics observed in individual neurons. Equivalent reduced models, like
the “leaky-integrate-and-fire” neuron, can then be used to give statistical
descriptions for the patterns of spikes typically recorded in EEG data.
Workshop presentations in this area included talks by Robert Kass (Carnegie
Mellon), Kenneth Miller (Columbia) and Uri Eden (Boston Univ).

Returning to studies at the “whole-brain” level, many speakers touched on
the computational challenges involved in analyzing the huge datasets that
have been collected in connection with some clinical studies. The importance
of using mathematical and statistical methods to interpret clinical
neuroscience was also highlighted in talks on neurodevelopment by Raquel Gur
(Univ Pennsylvania), behavioral studies by Ruben Gur (Univ Pennsylvania)
and the influence of anesthesia on brain activity by Emery Brown (Harvard).

two people looking at the poster

Looking at a poster during the CCNS Opening Workshop.

Many of the advanced topics addressed in the workshop were also introduced
in a Neuroscience Summer School that was held in connection with the CCNS
program in July. The research focuses begun in the workshop are being
carried forward in several working groups, two graduate courses and further
workshops