By Jennie Dorris

Barack Obama has just been introduced as the “scientist in chief.” He begins his remarks by joking that he’s thankful for the promotion. “Given my grades in physics, I’m not sure it’s deserved,” he adds. Everyone chuckles.

It’s spring 2013 in the East Room of the White House, and the president of the United States is announcing “the next great American project”—the BRAIN Initiative: “As humans, we can identify galaxies light years away, we can study particles smaller than an atom. But we still haven’t unlocked the mystery of the three pounds of matter that sits between our ears.”

The BRAIN Initiative, which stands for Brain Research through Advancing Innovative Neurotechnologies, will change how we understand the brain. To do so, the president knows he needs help: “We’re also partnering with the private sector, … including research institutions to tap the nation’s brightest minds to help us reach our goal.”

V12n1 F3 1Carnegie Mellon has responded to Obama’s call to action with BrainHub, an initiative to use technology to understand the brain. The research is collaborative on multiple levels—across the fields of computer science, neuroscience, psychology, and engineering. The partnerships also extend outside CMU—to the University of Warwick, which is developing digital health technology; Sun Yat-sen University, which is studying immunotherapy treatments for patients with Alzheimer’s disease; Oxford University, which houses the multidisciplinary International Brain Mechanics and Trauma Lab; and the Indian Institute of Science, which launched the Centre for Neuroscience to bring together its departments of engineering, math, physics, and biology to study the brain.

CMU’s BrainHub fills its own specific role through three initiatives: designing new tools to measure the brain, developing new methods to train the brain, and creating new computational methods to analyze data on the brain. BrainHub is supported for the next five years by $75 million from multiple sources, including Henry L. Hillman, R. K. Mellon Foundation, the Dietrich Foundation, and Kris Gopalakrishnan, co-founder of Infosys. The support will help, among other areas, graduate fellowships in brain research and provide seed grants for innovative research projects.

Each area of research highlighted by the BrainHub isn’t new; in fact, most of it is well underway and has been for years at CMU. Behind each topic are teams of researchers who have been part of the Center for the Neural Basis of Cognition, a joint venture between CMU and the University of Pittsburgh.

Carnegie Mellon Today asked three of these teams to open their labs and show us the research that is helping us learn more about the brain.

Brain Training
On a computer screen is a 1980s-style arcade game. Intermittently, a strange sound blares and an alien appears. Then a spaceship pops up. Those playing the games are told their job is to win the game by shooting aliens and capturing spaceships.

What they don’t know is that Professor of Psychology Lori Holt, who specializes in how people hear spoken language, has designed this game to study the learning of speech patterns by creating her own soundtrack. “Sometimes it mimics the structure of speech, and sometimes we use actual speech,” she says.

When participants see an alien, for example, they hear a specific sound. As the game gets faster, the sound is a continued cue that the alien is going to appear, and the player can start to anticipate how to react. However, if those sounds are turned into specific speech sounds, Holt says, the participants are doing more than just playing a video game—they may be learning a new language.

An example is native Japanese adults who struggle with hearing and saying the difference between the “r” and “l” sounds in English. “They can be trained for many weeks yet only make modest gains,” Holt says. Could her video game get better results?

The Japanese-speaking volunteers didn’t know they would be learning about the two English sounds in Holt’s lab. They were simply asked to play the Space-Invaders-style game. When one alien appeared on the screen, the accompanying sound was “ra, ra, ra.” Another alien always cued “la, la, la.” It wasn’t until the end of the game that they were tested on whether they could hear the difference between “r” and “l.”

Holt reports major success—the participants learned in two and a half hours what had been taking weeks of studying. Her lab is, in effect, developing a new way to train the brain more efficiently by tapping into indirect learning through sounds.

The research stretches beyond learning a new language to help those who have learning disabilities. She is working on a simplified tool that captures the essential elements of the game that could be used with children to test whether they are hearing different categories of sound and determining whether they need additional practice learning speech sounds. She also wants to test patients with brain degeneration, hoping to uncover the brain mechanisms that play a role in learning through sound.

As Holt continues her research, she wants to determine whether people who learn speech patterns using this style of training retain the knowledge long term. The findings will help her determine rehabilitation strategies for those with language and neurodegenerative disorders.

Sorting the Data
Byron Yu, through collaborating with experimental neuroscientists, is studying how the brain’s activity guides movements. It’s possible thanks to brain computer interface (BCI)—electrodes attached to the brain that show the activity of the neurons.

Yu says the way the brain looks when we imagine making a movement is similar to how the brain looks when we’re trying to initiate movement. And that has great significance for those who need help with the movement of their limbs.

“It’s one of the major ways to eventually help paralyzed patients and amputees—they think about something moving and something moves in the outside world, whether it be a cursor or a robotic arm,” says Yu, an assistant professor in the Electrical and Computer Engineering department. His team develops the mathematical algorithms that help researchers study the brain.

Jan Scheuermann didn’t know about this research when she signed up to be part of a study at UPMC. At age 36, she was a party planner and mother of two children when she noticed her legs weren’t moving normally. Within two years, spinocerebellar degeneration, a genetic disease, would leave her paralyzed from the neck down.

A team of University of Pittsburgh medical researchers could see in Scheuermann’s brain—specifically, they could investigate the area that controlled her right arm’s movement. Scheuermann would imagine movement, like closing her hand into a fist, and the scientists could see the patterns coming through on the BCI.

When they hooked up the robotic arm, sure enough, her intent to move was translating into actual movements. Soon, she was able to move the hand up and down. Later, she mastered giving high fives. And finally, she attempted feeding herself. She looked at a small square of chocolate, concentrated, and moved the arm to the chocolate, closed the robotic fingers around it, and carefully brought it all the way to her mouth, taking a bite.

While Yu is clear to point out that the research was conducted by the University of Pittsburgh team, he was thrilled to see how the basic scientific studies he and others in the field are pursuing are being translated to help human patients—with nearly two million people in the United States alone living as amputees, and 150,000 with quadriplegia, this research is providing life-changing hope to many.

The reach of his algorithms doesn’t stop there. He says his work with BCIs can similarly help patients with strokes and neurodegenerative diseases. He is currently using a technique called dimensionality reduction to study how the brain learns and identify the differences in activity between healthy and abnormal brains. He hopes that this research can, as it did with Scheuermann, find its way to human patients and help them regain function.

The Tools
Marcel Bruchez is looking at a tiny protein that glows in the dark. He’s used to being able to tell where proteins go in brain cells from these fluorescent tags, but today something is different. Now, instead of learning about the protein the tag is attached to, he’s able to learn how this protein is controlled by other proteins around the brain. This was an accident, but he already knew it might lead to some answers.

“We scratched our heads and said, ‘That’s interesting; where could we find an important application for it?’”

Bruchez—who is a CMU associate professor in the Biological Sciences and Chemistry departments and the director of the Molecular Biosensors and Imaging Center—decided to walk down the hall. He didn’t have to go far; just a few doors down is Professor Alison Barth, who has a problem. Her lab is studying epilepsy, particularly why a person who has one seizure has a higher likelihood of having a second. She needs to study a particular ion channel, which she suspects could be linked to epilepsy, but the tool she has isn’t showing her what she needs. What Bruchez had discovered in seeing the control provided by other proteins, was exactly what she was looking for. It was almost easy.

“She told me she had a problem just after I had found the right approach. It was a natural connection,” Bruchez says of the collaboration.

The small, glowing protein was the first step in Bruchez being able to answer Barth’s question. They wrote and received a grant from the NIH to keep developing the technology, and subsequently Barth’s team was able to better see how the ion channels in overly excited neurons were playing a role in epileptic seizures.

Bruchez’ role in the research is like that of a general contractor, or, as he says, a “tools developer.” He often feels like he’s metaphorically carrying around a hammer. And no one, he laughs, has more nails than the neuroscientists who work close to him.

“You can’t walk into a neuroscientist’s lab without them saying, ‘God, I wish we could see this,’” he says. Often, as a general contractor, his job is to build windows into the brain, carefully trying to make the view as clear as possible.

His research won’t just help Barth with epilepsy; this type of research also has implications for Parkinson’s disease and Alzheimer’s treatments.

Right now, research shows that patients with Parkinson’s disease lose a type of neuron in the part of their brains that produces dopamine. The lack of dopamine affects the area of the brain that produces movement. Bruchez is thinking beyond just researching the loss of neurons, however, and wants to look to the connection between those neurons.

Parkinson’s symptoms don’t show up until a patient loses a certain amount of neurons. But if we watch the synapses between the neurons, we can see that when their connections change, it can be an ideal time to offer an intervention to slow the changes and delay the onset of Parkinson’s disease. It’s a similar story with Alzheimer’s disease; Bruchez is working to scrutinize these networks that can predict the arrival of symptoms.

“It may be difficult to save the loss of neurons, but maybe we can treat it with something that enhances the strength or number of synapses to delay the onset of symptoms of Parkinson’s,” he says.

It didn’t take long for the work at CMU to be recognized. In late September, a team from the university visited the White House for an event about the progress of the BRAIN Initiative. They were in good company: They were joined by Google, General Electric, and the Food and Drug Administration, among others, who are working to expand research on the brain.

There was good news—the National Institutes of Health announced $46 million in new funds to support the initiative, and private companies pledged $270 million in research investments. President Obama was pleased: “I’m heartened to see so many private, philanthropic, and academic institutions joining this effort.”