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Miller Lab


My recent experimental and theoretical studies have been focused on an analysis of the "codes" with which nerve cells in sensory systems represent information about external stimuli, the neural mechanisms through which that information is processed within subsequent stages of the nervous system, and the extent to which the nervous system may have become optimized through evolution.

My recent experimental and theoretical studies have been focused on an analysis of neural coding in the cricket cercal sensory system. The general problem has been broken down into several distinct questions related to aspects of the observed stimulus/response characteristics of the neurons: 1) What parameters of sensory stimuli are encoded in the spike trains of the receptors and first order sensory interneurons in this system? 2) What is the theoretical limiting accuracy with which those parameters could be decoded from the neuronal spike trains? 3) How is the information encoded within different aspects of the spike train patterns? 4) What are the structural and biophysical mechanisms through which the observed coding scheme is implemented within this neural network?

In collaboration with Dr. Tomas Gedeon in the Department of Mathematical Sciences, I am also studying the extent to which the structure and function of the cricket cercal sensory system may have been optimized, through evolution, to be more efficient from the standpoints of neural computation and sensitivity.

My general approach is to integrate electrophysiological experimental recording techniques with advanced mathematical analysis techniques toward a rigorous characterization of the neural encoding schemes. Electrophysiological approaches techniques include intracellular microelectrode recording and multi-unit extracellular recording. The major analytical techniques I have used include compartmental modeling of single identified nerve cells and a branch of multivariate statistics called "information theory."



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Last updated: 2011-08-08T01:03:51.431-05:00

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The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016