Jerry Chen, a Boston University College of Arts & Sciences assistant professor of biology, has always had a busy schedule. Now, thanks to a major grant from the National Institutes of Health, it’s going to get even busier. On October 2, 2018, the National Institutes of Health announced that Chen is the winner of the 2018 New Innovator Award of $2.5 million over the next five years. That money will fund Chen’s efforts to crack the neural code of the brain and better understand the relationship between the genetic and electrical influences that control cognitive functions like sensory processing, decision-making, and learning and memory.
Chen’s New Innovator award is one of four High-Risk, High-Reward Research Awards presented annually by the NIH, and honoring high-impact programs that cross NIH institutes and centers. The award supports unusually innovative research from early-career investigators who are within 10 years of their final degree or clinical residency and have not yet received a research project grant or equivalent NIH grant. Chen, who came to BU from the University of Zurich, Switzerland, three years ago, also won the 2016 Stuart and Elizabeth Pratt Career Development Professorship, which highlights excellence within CAS.
“It’s an honor to receive this New Innovator Award,” says Chen. “There are few other opportunities out there where we can really try something that is both risky but also has the potential to have a big impact in understanding how the brain works.”
Gloria Waters, vice president and associate provost for research at BU, says it’s wonderful to see junior faculty who have received internal awards now receive external recognition for their work. “An award such as this is particularly impressive,” she says. “It signifies that Jerry is truly doing cutting-edge work that could have a huge impact on his field.”
“In order to crack the neural code,” says Chen, “you need to know at least two things. First, you need to be able to measure the activity of neurons in the brain as a subject is carrying out different cognitive tasks. And second, you have to know which genes are involved with that activity.”
To do that, researchers in Chen’s lab first use microscopes and imaging technology to measure the activity of the neurons as they fire in a mouse brain. The problem, says Chen, is that all neurons are not the same. “If you think about the brain as a complex computer or circuit, there are many different components that make up a circuit board and they all serve different functions,” he says. So researchers then perform a postmortem examination of the brain and attempt to identify which genes are being expressed in which cells.
“Measuring the molecular composition of each neuron can inform us what kind of component that neuron is in the circuit,” he says. “What we’re trying to do is establish an experimental platform that will allow us to put these two types of information together—measure the activity of neurons in the brain and then determine the molecular composition of those same neurons. The platform will help us understand the neural code and the specific circuits that can generate that code.”
That platform, says Chen, will help reveal how gene expression can define circuits in the brain’s neocortex and their computations. Ultimately, Chen hopes to understand which circuits and computations in the brain are genetically defined, or “hardwired,” and which can have the ability to adapt and change as a result of learning and memory.