Unlocking the Secrets of the Brain
Why do some people learn faster than others? Professor Byron Yu works on solving these and other mysteries in his BME laboratory.
Professor Byron Yu has always been interested in how learning takes place. “When learning to play tennis or golf, I always found it frustrating that I could do something successfully just once,” he says. “Yet I was watching athletes on TV do the same thing over and over. Why was it so easy for them to learn the correct mechanics of a swing or a forehand — yet so challenging for me?”
After completing a B.S. in Electrical Engineering and Computer Sciences from the University of California, Berkeley, and an M.S. in Electrical Engineering from Stanford University, Yu was torn between working in industry and pursuing a Ph.D.
“I only wanted to invest years in doctoral research if it was a subject I was passionate about,” Yu recalls. “When I met a professor at Stanford who specialized in neuroscience, I realized it was tied to my own curiosity about how the brain works — and I was hooked. As a Ph.D. researcher, I was so excited about my work that I got up every morning before my alarm went off. I couldn’t wait to get to the lab.” Yu completed his Ph.D. in 2007 and joined the CMU faculty in 2010.
Today Yu — who holds joint appointments in Biomedical Engineering (BME) and Electrical and Computer Engineering (ECE) — brings that same passion to his own lab at Carnegie Mellon.
He and his collaborators — including Professors Steven Chase (BME), Aaron Batista (University of Pittsburgh), and Matthew Smith (University of Pittsburgh) — seek to unlock the secrets of brain activity in order to develop improved teaching techniques based on how the brain actually processes signals. By studying neuron patterns in the brain, Yu is increasing the shared understanding of how learning occurs — and why some educational techniques are more effective than others.
“The signals transmitted and processed by the brain are like Morse code,” explains Yu. “It’s our job to break this code and reveal exactly how these signals relate to physical movement or improved cognition. This new understanding can help people learn a sport more effectively, or improve their problem-solving abilities in an academic subject like math.”
Yu’s research also supports the development of brain-computer interfaces that directly translate thoughts into physical actions. These tools help disabled or paralyzed people move computer cursors or robotic arms just by thinking about the movement.
According to Yu, Carnegie Mellon and the Department of Biomedical Engineering represent the perfect environment to carry out this critical research. “First of all, there is a wealth of groups at CMU in relevant fields, including neuroscience, engineering, computer science, and statistics,” he says. “Second, CMU encourages collaboration at an institutional level. These collaborations have been essential to our research.”
Yu also credits CMU and BME for their willingness to form academic partnerships that advance the state of biomedical research. One example is the Center for the Neural Basis of Cognition, a joint venture of the University of Pittsburgh and Carnegie Mellon. This center leverages the strengths of the University of Pittsburgh and CMU to support a coordinated cross-university research and educational program in neuroscience of international stature.
“Carnegie Mellon really encourages the kinds of academic and scientific partnerships that drive innovation, and I’m happy to be a part of that environment,” notes Yu. Professor Yu’s research is supported by the National Institutes of Health, the National Science Foundation, and the Simons Foundation.