Emery Brown

Core Faculty
Phone: (617) 324-1880
Lab Phone: (617) 324-1881
room: 46-6079A
MIT address: 77 Massachusetts Ave., Cambridge, MA 02139
Administrative Assistant: Sheri Leone
assistant phone: (617) 324-1879
assistant email: sheri@neurostat.mit.edu

Emery Brown

Core Faculty

title(s)

  • Edward Hood Taplin Professor of Medical Engineering and of Computational Neuroscience, Massachusetts Institute of Technology
  • Professor of Health Sciences and Technology, Massachusetts Institute of Technology
  • Warren M. Zapol Professor of Anaesthesia, Harvard Medical School, Massachussetts General Hospital
  • Director, Harvard-MIT Health Sciences and Technology Program, MIT
  • Associate Director, Institute for Medical Engineering and Science, MIT
  • Investigator, Picower Center for Learning and Memory, Department of Brain and Cognitive Sciences, MIT

degrees

  • PhD in Statistics, Harvard University, 1988
  • MD, Harvard Medical School, 1987
  • AM in Statistics, Harvard University, 1984
  • BA, Harvard College, 1978

selected awards/societies

  • 2016 Fellow, Institute of Mathematical Statistics
  • 2015 Fellow, National Academy of Inventors
  • 2015 American Society of Anesthesiologists Award for Excellence in Research
  • 2015 Member, National Academy of Engineering
  • 2015 Guggenheim Fellow in Applied Mathematics
  • 2014 Member, National Academy of Sciences
  • 2012 NIH Director’s Transformative Research Award
  • 2012 Fellow, American Academy of Arts and Sciences
  • 2011 National Institute of Statistical Science, Jerome Sacks Award
  • 2008 Fellow, IEEE
  • 2007 Member, National Academy of Medicine
  • 2007 NIH Director’s Pioneer Award
  • 2007 Fellow, American Association for the Advancement of Science
  • 2006 Fellow, American Statistical Association
  • 2006 Fellow, American Institute for Medical and Biological Engineering
  • 2002 Member, Association of University Anesthesiologists

research

Neural Signal Processing Algorithms

Recent technological and experimental advances in the capabilities to record signals from neural systems have led to an unprecedented increase in the types and volume of data collected in neuroscience experiments and hence, in the need for appropriate techniques to analyze them. Therefore, using combinations of likelihood, Bayesian, state-space, time-series and point process approaches, a primary focus of the research in my laboratory is the development of statistical methods and signal-processing algorithms for neuroscience data analysis. We have used our methods to characterize:

  • how hippocampal neurons represent spatial information in their ensemble firing patterns
  • analyze formation of spatial receptive fields in the hippocampus during learning of novel environments
  • relate changes in hippocampal neural activity to changes in performance during procedural learning
  • improve signal extraction from fMR imaging time-series
  • construct algorithms for neural prosthetic control the spiking properties of neurons in primary motor cortex
  • localize dynamically sources of neural activity in the brain from EEG and MEG recordings made during cognitive, motor and somatosensory tasks
  • measure the period of the circadian pacemaker (human biological clock) and its sensitivity to light
  • characterize the dynamics of human heart beats in physiological and pathological states
  • track brain states under general anesthesia

Understanding General Anesthesia

General anesthesia is a neurophysiological state in which a patient is rendered unconscious, insensitive to pain, amnestic, and immobile, while being maintained physiologically stable. General anesthesia has been administered in the US for more than 165 years and currently more than 60,000 people receive general anesthesia daily in this country for surgery alone. Still, the mechanism by which an anesthetic drug induces general anesthesia remains a medical mystery. We use a systems neuroscience approach to study how the state of general anesthesia is induced and maintained. To do so, we are using fMRI, EEG, neurophysiological recordings, microdialysis methods and mathematical modeling in interdisciplinary collaborations with investigators in HST, the Department of Brain and Cognitive Sciences at MIT, Massachusetts General Hospital, and Boston University. The long-term goal of this research is to establish a neurophysiological definition of anesthesia, safer, site-specific anesthetic drugs and to develop better neurophysiologically-based methods for measuring depth of anesthesia.

selected publications

A full list of Dr. Emery Brown’s publications can be found on his website.

courses taught

  • HST 460 – SP 2013 – Statistics for Neuroscience Research
  • HST 576 – SP 2013 – Topics in Neural Signal Processing