Welcome to NSRL @ 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

    • 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 drug-induced, reversible state consisting of unconsciousness, anti-nociception (being insensate), amnesia (inability to form memories), akinesia (lack of mobility) while maintaining control of vital physiology such as the cardiovascular system, respiratory system and the stress response. With the advent of general anesthesia more than 170 years ago, surgery was transformed overnight from a barbaric spectacle to a safe and humane therapeutic intervention. Each year,100 million people world-wide receive general anesthesia to undergo surgery or invasive diagnostic procedures. When the formal practice of anesthesiology began after the first public demonstration of ether anesthesia at Massachusetts General Hospital in 1846, the general anesthesia was maintained by administering this single agent. Today, the modern practice of anesthesiology uses balanced anesthesia in which multiple drugs are administered simultaneously to achieve the anesthetic state. For example, propofol or an inhaled ether, such as sevoflurane, is given to induce and maintain unconsciousness and amnesia; opioids and/or other pain medications are used to maintain anti-nociception; and anticholinergic agents are given to maintain muscle relaxation or akinesia. Over time, anesthesiologists have learned that the advantage of balanced general anesthesia is that it is possible to achieve the desired effects of the agents using smaller doses, and hence, fewer of the side effects.


MIT 9.07 – Statistics for Brain and Cognitive Sciences

MIT 9.073/ HST 460 – Statistics for Neuroscience Research

MIT 9.272J, HST.576J – Topics in Neural Signal Processing

HST 500 – Frontiers in (Bio) Medical Engineering and Physics

HST/S56 Special Subject: Introduction to Closed-Loop Control of Physiological Systems. Term: IAP. Course Website: http://stellar.mit.edu/S/course/HST/ia19/HST.S56/