Title

Parameter Optimization for Excitable Cells

Presentation Type

Poster

Faculty Advisor

Eric Forgoston

Access Type

Event

Start Date

26-4-2023 12:30 PM

End Date

26-4-2023 1:30 PM

Description

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 using a system of nonlinear differential equations. Later, Schild et al. 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 sufficiently characterize electrical signatures of nodose neurons.

This document is currently not available here.

COinS
 
Apr 26th, 12:30 PM Apr 26th, 1:30 PM

Parameter Optimization for Excitable Cells

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 using a system of nonlinear differential equations. Later, Schild et al. 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 sufficiently characterize electrical signatures of nodose neurons.