Emery N. Brown, MD, PhD
Core Faculty
Edward Hood Taplin Professor of Medical Engineering, MIT
Professor of Health Sciences and Technology, MIT
Professor of Computational Neuroscience, MIT
Warren M. Zapol Professor of Anaesthesia, Harvard Medical School, Massachusetts General Hospital
Investigator, Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT
Emery Brown
Email
enb [at] neurostat.mit.edu
Website
Neuroscience Statistics Research Lab
Phone
(617) 324-1880
Lab Phone
(617) 324-1881
Address

77 Massachusetts Ave.

Cambridge, MA 02139

Room
46-6079A
Administrative Assistant(s)
Rhonda Valenti, Laboratory Administrator
617-840-7287
rvalenti [at] mgh.harvard.edu
Emery N. Brown, MD, PhD
Core Faculty
Edward Hood Taplin Professor of Medical Engineering, MIT
Professor of Health Sciences and Technology, MIT
Professor of Computational Neuroscience, MIT
Warren M. Zapol Professor of Anaesthesia, Harvard Medical School, Massachusetts General Hospital
Investigator, Picower Institute 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

Bio

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 175 years and currently more than 100,000 people receive general anesthesia daily in this country for surgery alone. The mechanisms by which anesthetic drugs induce altered states of arousal are now being defined neurophysiologically. 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, micro dialysis 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 level of unconsciousness.

Selected Awards/Societies

  • 2022 Gruber Neuroscience Prize
  • 2022 Pierre M. Galletti Award, American Institute for Medical and Biological Engineering
  • 2020 DeWitt Stetten Lecture, National Institute of General Medical Sciences
  • 2020 Swartz Prize for Theoretical and Computational Neuroscience
  • 2020 John and Elizabeth Phillips Award, Phillips Exeter Academy
  • 2019 Doctor of Science Honoris Causa, University of Southern California
  • 2019 Tatiana Pérez de Guzmán el Bueno Lecture (in Spanish), Universidad Autónoma de Madrid
  • 2018 Dickson Prize in Science
  • 2018 Member, Florida Inventors Hall of Fame
  • 2017 Medallion Lecture, Institute of Mathematical Statistics
  • 2017 Severinghaus Lecture on Translational Science, American Society of Anesthesiologists
  • 2017 Fellow, International Academy of Medical and Biological Engineering
  • 2016 Fellow, Institute of Mathematical Statistics
  • 2015 Fellow, National Academy of Inventors
  • 2015 Award for Excellence in Research, American Society of Anesthesiologists
  • 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 Jerome Sacks Award for Cross-Disciplinary Research, National Institute for Statistical Science
  • 2008 Black Enterprise Magazine, America’s Leading Doctors
  • 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

Selected Publications

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

Courses Taught

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