The Mathematical Biology and Dynamical Systems Seminar series presents Dr. William Holmes discussing “Fitting Parameter Values for Use in Neuron Models: A Primer” on Tuesday, April 24, from 3:05 to 4 p.m. in Morton 326.
Holmes is Professor of Biological Sciences and the retiring director of the Quantitative Biology Institute.
“After the presentation, please join us at 4 p.m. for coffee and cookies in 325 Morton Hall to show our appreciation of Dr. Holmes’ dedicated service to the Quantitative Biology Institute, to celebrate our accomplishments in AY 2017-18, and to discuss the future of the QBI and of our seminar,” says Dr. Winfried Just, Professor of Mathematics.
Abstract: To study individual neurons with models, it is necessary to have values for model parameters. In particular, we need values for Rm, Ra, Cm, all of the conductance densities and the V1/2 and slope factors for each ion conductance and more. Then there is the issue of cell morphology. Complex models can have hundreds or thousands of degrees of freedom, and to get anything useful out of a model, we need to constrain parameter values as best as possible from experimental data. One way to obtain parameter values is to fit a model to a set of experimental data, applying some type of criteria or fitness metric that measures distance or error between the model and the data. The choice of a distance metric is not obvious, but it should satisfy the triangle inequality and at the same time be robust to variations in experimental responses to the same stimuli. I will discuss different distance metrics and will introduce various approaches used to do parameter estimation for neuron models.
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