Date of Award

5-2023

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Applied Mathematics and Statistics

Thesis Sponsor/Dissertation Chair/Project Chair

Eric Forgoston

Committee Member

Elena Petroff

Committee Member

Baojun Song

Abstract

The electrophysiology of nodose ganglia neurons is of great interest in the analysis of cell membrane currents and action potential behavior. This behavior was initially outlined in the Hodgkin-Huxley conductance model [1] using a system of nonlinear differential equations. Later, Schild et al. [2] developed an extension of the Hodgkin-Huxley model to provide a more exhaustive description of ion channels involved in nodose neuronal action potential activity. We consider a variety of methods to fit the parameters of both the Hodgkin-Huxley and Schild et al. models to an empirical stimulus response dataset. Our methods were validated using synthetic datasets, as well as voltage-clamp data for nodose neurons. The fitting procedure that we implemented demonstrates the predictive efficacy of the Schild et al. model as well as its ability to provide a superior characterization of electrical signatures of nodose neurons.

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