Hackathons are old news in the computer world, but the concept has been given a new spin at Carnegie Mellon University with its first NeuroHackathon, a competition created to glean insights about the human brain and complement the work of BrainHub, the university’s multidisciplinary brain research center.

Hackathon, a blend of “hacking” and “marathon,” is an event where participants engage in round-the-clock programming.

Alison Barth, professor of biological sciences and interim BrainHub director, and Geoff Gordon, associate professor of machine learning, developed the contest to provide students with the scientific freedom to find patterns in data rather than seek a specific outcome. Barth and Gordon solicited faculty datasets and student participants that ranged from information related to links between brain region and illness to pathways in the brain.

“It was really exciting to help bring Alison and Geoffs idea to life and advance brain science in a completely new way,” said Gerry Balbier, executive director of BrainHub.

The response to tackle the data was strong: five teams entered, all current or former Ph.D. students at CMU who hoped to discover something new.

The Starting Line

Mariya Toneva, a Ph.D. student in CMU’s Machine Learning Department, had never done a hackathon, never seen the datasets and never worked with most of her teammates. But she was not intimidated; instead, she was thrilled by the chance for novel interactions.

Originally from Bulgaria, Toneva was a math whiz, winning multiple competitions in middle school and high school. She recalls sitting in a cognitive science class during her freshman year at Yale University, learning about memory. At one point her professor said, “We don’t know yet” — and this idea of unknown frontiers was in stark, fascinating contrast to the 200-year-old theorems Toneva used in math. Since those undergraduate days, she has wanted to combine computer science with cognitive science to better understand the brain. She saw collaborative possibilities through the Center for the Neural Basis of Cognition that she did not see elsewhere and the joint Ph.D. program in neural computation and machine learning was a natural fit.

The NeuroHackathon — hosted by BrainHub and sponsored by Qualcomm as well as by Google, Baidu, Microsoft, CMU Provost’s Office and the Department of Machine Learning — was a challenge she couldn’t refuse.

To start, faculty presented their datasets as students considered which to select. Almost like contestants on the dating game, they described the seductive features of their data then waited to be chosen.

Barth presented “Cell-type Identification Through Electrophysiological Fingerprinting.” If 80 billion neurons in the human brain could be labeled better, she said, then we’ll gain more insight into the computations carried out by these neurons.

Sandra Kuhlman, assistant professor of biological sciences, and Steve Chase, assistant professor in the Center for the Neural Basis of Cognition and biomedical engineering, provided data from a mouse’s motor cortex and asked participants to determine what direction the mouse was running based on the neural activity.

Andreas Pfenning, assistant professor in the Computational Biology Department, contributed data intended to find links between brain region and illness.

Toneva and her teammates were inspired by “Human Brain Neuroanatomy from MRI Images.” This dataset’s creators were Tim Verstynen, assistant professor of psychology, and Aarthi Singh, the A. Nico Habermann Associate Professor in the Machine Learning Department. They mapped the brain’s pathways using MRI data. Just as a computer can identify a face in a photograph — for instance, Facebook suggests tags when it recognizes your friends or family — Verstynen and Singh wanted to know if machines can learn to automatically identify labeled pathways in the brain.

They’re Off!

“Coin Toss,” which along with Toneva included Avinava Dubey from machine learning, Jay-Yoon Lee from computer science, Dan Schwartz, from language technology, and Ying Yang, from neural computation and machine learning. The group gathered in an office and looked at Verstynen and Signh’s list of 3-D trajectories in the brain.

In the wee hours of the morning, BrainHub supplied coffee and M&Ms, and the students supplied the brainpower. Team “Reckless Arrogance” changed its name to “Cautious Humility.”

By morning, the white boards were covered with graphs and equations. Participants worked through the night. Laptops were open, and phones were recording the presentations. One participant frantically watched his screen, waiting for data to load for his team’s presentation. The audience included BrainHub steering committee members, faculty, sponsors, competitors and judges.

The judges — Aryn Gittis, assistant professor of biological sciences; Jordan Rodu, visiting assistant professor of statistics; and Gordon — determined the winner by looking for three elements: the portability of a team’s approach; the rigor and appropriateness of analytical methods; and the potential for the findings to impact the fields of machine learning, computer science and/or neuroscience.

The Big Finish

Toneva presented Coin Toss’s findings where the team considered data for 129,414 brain trajectories and looked for ways to label tracks. The algorithm they developed enabled a computer to identify and label 55 types of nerve fiber bundles. The results were accurate 85 percent of the time.

Verstynen said the team’s solution for his dataset was simple, elegant and accurate.

“[They] looked at the problem from a very different perspective than we had in the lab,” he said.

Their solution could speed up the pace of brain mapping, something applicable in the real world: Mapping a typical brain and observing its connections can help further understanding disorders such as Alzheimer’s disease or schizophrenia, or help neurosurgeons determine the optimal trajectory for cutting into the brain.

Qualcomm Senior Director Rajesh Kumar noted the teams’ rigor and ability to achieve results in a short period of time.

“There’s a huge appetite” for this type of event, Barth said.

Toneva said she would definitely participate again.

“We did pretty well,” Toneva said, “but now we want to know how to do better.”

Video of the teams beginning to work »
Final presentations, part one »
Final presentations, part two »
More about the event »


Main photo caption: The winning "Coin Toss" team members: First row (L-R): Avinava Dubey, Jay-Yoon Lee; Second row (L-R): Ying Yang, Ahmed Hefny, Dan Schwartz, Mariya Toneva