Neural Dynamics: Theory and Modeling
Instructor: Stephanie R. Jones
Our thoughts and actions are mediated by the dynamic activity of the brain’s neurons. This course uses mathematics and computational modeling as a tool to study neural dynamics at the level of signal neurons and in more complicated networks. We focus on relevance to modern day neuroscience problems with a goal of linking dynamics to function. Topics include biophysically detailed and reduced representations of neurons, bifurcation and phase plane analysis of neural activity, and neural rhythms. This course is run through the Applied Mathematics Dept but is designed for a wide audience of advanced undergraduate or graduate students. The course compliments NEURO 1440 (Neural Dynamics), however no neuroscience background is required. Prerequisites include a class in differential equations and a Matlab programming course, or equivalent.
Next offering: Fall 2018