Reaching into an Abyss – Challenges in Computational Neuroscience and Graduate School

group shot of students at SAMSI

Students attending the Undergraduate Workshop at SAMSI.

The following was written by Praveen Suthaharan, an undergraduate student from North Carolina State University who recently attended the SAMSI Undergraduate Workshop on Computational Neuroscience.

Continually baffling researchers across the globe, the 3 pounds of matter that sits in our skull holds many mysteries that have yet to be discovered. Brain research, or Neuroscience, is on the verge of revolutionizing our world. In the past few years, by taking advantage of the advancements made in the computing world, several neuroscientists have delved into the brain trying to unfold many of its hidden intricacies. I, too, aspire to be part of this rising era of computational neuroscience research.

I’m an undergrad, majoring in Statistics and Neurobiology, at North Carolina State University. I plan to pursue a PhD in Computational Neuroscience. My exposure to the coursework in Statistics and Neurobiology has made me curious about the areas of study that lie at the intersection of the two fields. This curiosity has led me to steadfastly chase the inevitable question of, what IS computational neuroscience? This year’s SAMSI undergraduate workshop has served as a portal for me to explore this question that stemmed from my curiosity.

It was a Saturday morning and I could see new prospects for my future as I stepped into SAMSI and grabbed my official name tag. My pulse rate started beating fast, with a sense of excitement, as I walked into the conference room to a group of other dedicated and driven prospective scientists. The series of presentations started with a high note as Dr. Ciprian Crainiceanu began his talk with a tutorial on clinical brain imaging. Given the time, he provided a fast-paced, yet comprehensive lecture on ‘neurohacking’ and on the process of how brain images are coded into computable values for the purpose of monitoring/detecting changes in the brain. His presentation set the tone for our next presenter, Dr. Ana-Maria Staicu, who provided deep insight on the applications of an interesting image processing technique (anisotropic diffusion) on a well-known neurological disorder known as Multiple Sclerosis. At this very moment, as the momentum of wanting to think began to fade, I got distracted.

As the aroma of freshly baked bread hit my olfactory senses with a blast of pleasant sensation, I glanced at the time knowing it was lunch time. Immediately as we vacated the conference room, an announcement about taking a group photo was broadcasted to the students. We all congregated outside of SAMSI like any group of young, excited individuals – confused, yet composed.

people on the shuttle going to Duke University

Riding the bus to Duke.

With a blink of an eye, we were all set to board the shuttle to the Center of Neuroimaging at Duke. Here, we visited Dzirasa’s lab. We were all given an overview of the research lab and a tour of the facility. This visit has strengthened my interest in computational neuroscience research, and will be looking forward to applying to Duke for grad school.

Person talking at the Duke Lab

Stephen Mague talks to the students about Dzirasa’s Lab at Duke.

On our way back to SAMSI, the desire to acquire more knowledge grew inside of me as I was eager to learn about the applications of Fourier Transform (FT) within neuroscience, to interactively work with brain data using various programming languages, and to attend the graduate school panel discussion. Benjamin Risk, a postdoc who works at SAMSI, engaged us with a tutorial on image reconstruction using Discrete Fourier Transformation (DFT). The ability to manipulate images through mathematical approaches was mind-blowing, especially knowing that these approaches have been invaluable to neuroscience research. Following Benjamin’s talk, Sarah Vallélian introduced her presentation with a tutorial on Computed Tomography (CT). She discussed about several useful signal processing techniques, including back-projection, filtered back-projection, and Hilbert Transform, and gave us the opportunity to work with CT data using some of these techniques. As much as the other students enjoyed these presentations, I believe these interactive activities (i.e., using R, Matlab, and python) served as the best part of this workshop, allowing us to fiddle with the data and providing us with the initial steps to computational neuroscience research.

As the panel discussion about graduate studies commenced, my ears were engaged in the conversation as I was absorbing various useful information coming from insightful graduate students. I have come to realize that research mirrors an abyss – it’s a never ending path of glory. This appreciation of mine for research has now become my driving force to pursue graduate school. With that, the first day came to a close with an enticing dinner. The food formed this perfect taste combination that left my mouth revitalized and extremely satisfied. SAMSI definitely knows how to treat prospective scientists!

Ezra Miller, Duke, giving a lecture at the workshop.

Ezra Miller, Duke, giving a lecture at the workshop.

The next day ended with some more fascinating mathematical/statistical approaches to neuroscience as Dr. Laura Miller and Dr. Ezra miller took the floor. Particularly, Dr. Ezra Miller’s presentation on Topology for Statistical Analysis of Brain Artery Images provided me with a deeper insight on an interesting mathematical approach towards neuroscience. As a matter of fact, his presentation motivated me to immerse myself in Topology and its various applications to neuroscience.

With the end of my undergrad years, just around the corner, new doors to success have emerged with this amazing workshop. Not only did this workshop provide me with a new perspective on my research interest and grad school, but it has also given me the appreciation and audacity to reach into the abyss, knowing that it will lead me on a never ending path of glory. After all, research, in particular, computational neuroscience research, is an abyss – a bottomless pit filled with incessantly approaching questions that permeate your mind with curiosity of the mysteries of the brain.

SAMSI has organized an incredible workshop that I would not think twice about attending in the future.

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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.

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