Hang Lu, Ph.D. (Chemical and Biomolecular Engineering)
Robert Butera, Ph.D. (Electrical and Computer Engineering)
Patrick McGrath, Ph.D. (Biology)
Lena Ting, Ph.D. (Biomedical Engineering)
Patricio Vela, Ph.D. (Electrical and Computer Engineering)
Title: All-optical white noise analysis of mechanosensory neural circuits in Caenorhabditis elegans
The human brain is a system that processes sensory information from the environment to output behavioral responses. A fundamental question in neuroscience is how the neural circuitry calculates the appropriate output from a given input, or in terms of systems analysis, what are transfer functions that describe this system’s function? A key challenge in answering this question is the overwhelming complexity of this system. Another challenge is acquiring accurate output measurements while simultaneously controlling the input of the system. C. elegans serves as a useful model organism in answering this question by addressing and overcoming both of these issues. First, the C. elegans’ nervous system contains only 302 neurons, and is the only organism that has its entire connectome mapped. Second, it has easily manipulated genetics, high progeny number, and a transparent body, allowing for high-throughput calcium imaging, optogenetics, and behavior tracking experiments. In my thesis, I will develop a platform that can precisely control neuronal activity with optogenetics, while simultaneously measuring neuronal activity with calcium imaging and behavioral output with computer vision tools in order to perform white-noise analysis. This will allow for estimation of impulse responses that characterize C. elegans neural circuitry, providing accurate models of its function. This method will be applied to two mechanosensory circuits in order to compare their spatial and temporal properties.