Although both of his parents were math teachers, Emery Neal Brown was drawn more to romance languages than mathematics during his childhood in Ocala, Florida. Indeed, when he transferred to Phillips Exeter Academy in New Hampshire in his junior year of high school, he leapt at the chance to spend his last semester studying Spanish in Barcelona. Later that year, he entered Harvard College with the intention of majoring in romance languages and then going on to medical school, but late-night discussions with his roommates, who were economics majors, got him interested in statistics. “In my junior year, I decided to switch my major to applied mathematics, even though I hadn’t yet taken a single statistics course,” he recalls.
After graduation, Brown was awarded an International Rotary Foundation Fellowship to study mathematics at the Institut Fourier des Mathèmatiques Pures in Grenoble, France. When he returned to the States, he entered Harvard University’s MD-PhD program, receiving his medical degree in 1987 and his PhD in statistics in 1988. Brown did his internship in internal medicine at the Brigham and Women’s Hospital and his residency in anesthesiology at Massachusetts General Hospital (MGH), joining the staff of that hospital—and the faculty of Harvard Medical School—in 1992. “I enjoyed the fast pace and real-time physiology of anesthesiology,” he says. He also wanted a specialty that would give him predictable hours so he could continue his research interests.
Brown’s initial research effort involved developing statistical methods to analyze circadian rhythms. His methods helped establish many of the properties of the human circadian system, including the finding that the human circadian clock runs on a cycle closer to 24 than to 25 hours, as had been previously believed. By the mid-1990s, however, Brown decided to switch his focus. “I was looking for cool problems to solve with statistical methodology, and so I looked into neuroscience” he recalls. While studying computational neuroscience at the Marine Biological Laboratory at Woods Hole, Massachusetts, Brown devised a new approach to decoding the position of an animal in its environment by observing the ensemble activity of a small group of place cells in the animal’s hippocampus. The resulting state-space algorithm for point processes not only offered much better decoding with fewer neurons than previous approaches, but it also established a new framework for specifying dynamically the relationship between the spike trains (the timing sequence of firing neurons) in the brain and factors from the outside world. “One of the basic questions at the time was whether an animal holds a representation of where it is in its mind—in the hippocampus,” says Brown. “We were able to show that it did, and we could show that with only 30 neurons.”
After introducing this state-space paradigm to neuroscience, Brown went on to refine the original idea and apply it to other dynamic situations—to simultaneously track neural activity and learning, for example, and to define with precision anesthesia-induced loss of consciousness, as well as its subsequent recovery. In the early 2000s, Brown put together a team to specifically study anesthesia’s effects on the brain. “It was often stated that we do not know how anesthesia works, he says. “Nothing could be further from the truth.”
Through experimental research and mathematical modeling, Brown and his team showed that the altered arousal states produced by the main classes of anesthesia medications can be characterized by analyzing the oscillatory patterns observed in the EEG along with the locations of their molecular targets, and the anatomy and physiology of the neural circuits that connect those locations. He has established that a principal way in which anesthetics produce unconsciousness is by producing oscillations that impair how different brain regions communicate with each other. The result has been a new paradigm for brain monitoring during general anesthesia for surgery, one that allows an anesthesiologist to dose the patient based on EEG readouts (neural oscillations) of the patient’s anesthetic state rather than purely on vital sign responses. This pioneering approach promises to revolutionize how anesthesia medications are delivered to patients, and also shed light on other altered states of arousal such as sleep and coma.
In 2005, Brown joined the faculty at the Massachusetts Institute of Technology, where he is the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience. He also holds a chaired professorship, the Warren M. Zapol Professor of Anaesthesia, at Harvard Medical School. In addition, he spends one day a week as an anesthesiologist caring for patients in the operating room at MGH. Brown has received many awards and recognitions during his career, including memberships in the National Academy of Science, the National Academy of Medicine, and the National Academy of Engineering. In 2007, he was a recipient of the NIH Director’s Pioneer Award, which is given to innovative scientists who are doing high-risk, high-reward research. He also received the Excellence in Research Award from the American Society of Anesthesiologists, the Swartz Prize for Theoretical and Computational Neuroscience, the Dickson Prize in Science and the Pierre Galletti Award. Brown lives in the Boston area with his wife, Virginia Andradas, who is a public health nurse. They have two adult children.