Thesis/Capstone Archive

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Tyler Bahr (Senior Thesis, April 2018, Advisor: Mark Transtrum )


In 1952 Hodgkin and Huxley formulated the fundamental biophysical model of how neurons integrate input and fire electric spikes. With 25 parameters and 4 dynamical variables, the model is quite complex. Using information theory, we analyze the model complexity and demonstrate that it is unnecessarily complex for many neural modeling tasks. Using the manifold boundary approximation method of model reduction, we perform a series of parameter reductions on the original 25-parameter model and create a series of spiking Hodgin-Huxley models, each with decreasing parameter number. We analyze the physical meaning of some key approximations uncovered by our systematic reduction methods, which are "blind" to the real physical processes the model is intended to capture. We then evaluate the behavior of the most greatly reduced 14-parameter model under different experimental conditions, including networks of neurons. We also discuss new questions that have arisen as a result of our work