This is an application for a KO2 Independent Scientist Award. The candidate is an anesthesiologist/statistician whose research to date has focused on the development of statistical models for the quantitative study of how neural systems represent and transmit information the central focus of his career research. The study of how neural systems encode information is one of the most challenging and fascinating problems in science. The point process character of neural spike trains means that standard signal processing techniques developed to analyze continuous signals will have limited application in the analysis of neural systems. The study of neural signal processing requires the development of new quantitative techniques to accurately characterize the properties of neural systems. These methods should be developed in close collaboration with experimentalists to ensure that the models remain completely faithful to the neurophysiology. For this reason, the candidate will collaborate with Professor Matt Wilson in the Department of Brain and Cognitive Science at MIT. The research will use Professor Wilson's paradigm of simultaneous multiunit recordings of pyramidal (place) cells in the hippocampus of freely behaving rodents to model, how these neurons encode spatial information as the animals perform specific behavioral tasks. The statistical methods to be developed will be based on spatio-temporal point process models of hippocampal place cell spiking activity and nonlinear recursive filtering algorithms based on Bayesian statistical theory. The experimental work in this project will be carried out in Professor Wilson's laboratory at MIT and is an integral part of his research on characterizing the role of the hippocampus in short- and long-term memory formation. The methodology research will be conducted in parallel at the candidate's laboratory in the Department of Anesthesia at Massachusetts General Hospital. The candidate will use the additional funded research time provided by KO2 award to enhance his knowledge of hippocampus physiology and anatomy and to develop a sound theoretical framework based on theory of point processes from which to derive signal processing methods appropriate for neural systems. The candidate's long-term objectives are to continue his work on neural information processing and the study of the hippocampus in memory formation. The research to be undertaken in this project will also provide a set of statistical tools with which neuroscientists will be able to study information representation and transmission in neural systems using multiunit activity data recorded along with relevant biological signals.
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