Emery N. Brown, M.D., Ph.D.

Warren M. Zapol Professor of Anaesthesia, Harvard Medical School, Department of Anesthesia and Critical Care, Massachusetts General Hospital

Edward Hood Taplin Professor of Medical Engineering Institute for Medical Engineering and Science

Professor of Computational Neuroscience, Department of Brain and Cognitive Sciences, MIT

Professor of Health Sciences and Technology, Harvard/MIT Division of Health Sciences and Technology, MIT


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.
  • characterize 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.


Below are three animations showing decoding of a rat's position in its environment from simultaneously recorded spiking activity of CA1 place cell neurons in the animal's hippocampus.

Ensemble Neural Spike Train Decoding Video 1

Ensemble Neural Spike Train Decoding Video 2

Ensemble Neural Spike Train Decoding Video 3


Below are two animations that show tracking of  the temporal evolution of a simulated and an actual CA1 place cell's receptive field  using a point process adaptive filter algorithm with a Gaussian place field model and the assumption of inhomogeneous Poisson model for the neural spike trains.

Simulated CA1 Place Field Dynamics

Actual CA1 Place Field Dynamics

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 U.S. for nearly 160 years and currently, more than 50,000 people receive anesthesia daily in this country for surgery alone. Still, the mechanism by which an anesthetic drug induces general anesthesia remains a medical mystery. A new research direction in my laboratory is to 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 signal processing and mathematical modeling in interdisciplinary collaborations with investigators at Massachusetts General Hospital, the Harvard/MIT Division of Health Science and Technology, the Department of Brain and Cognitive Sciences at MIT, 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.


E-Mail: enb@neurostat.mit.edu   
Phone: (617) 726-7487