Neur 1440: Mechanisms and Meaning of Neural Dynamics
Instructor: Dr. Stephanie R. Jones
Next available: Fall 2023
Prerequisites: Prerequisites: NEUR 0010 or minimum score of WAIVE in 'Graduate Student PreReq'
We humans can shift our attention, perceive new objects, make complex motions, and adjust each of these behaviors within factions of a second. Neurons and systems of neurons vary in their activity patterns on millisecond to second time scales, commonly referred to as "neural dynamics." This course addresses mechanisms underlying this flexibility and its potential meaning for information processing in the brain. The course integrates biophysical, computational, single neuron and human studies. In addition to lectures and readings, students will learn how to build computational models to simulate neural dynamics at various scales from single neurons to networks, using Matlab and the Human Neocortical Neurosolver. Computational modeling will be taught hands-on in an interactive lab session each week. Please request override through Courses@Brown.
AMPA 2821V: Neural Dynamics: Theory and Modeling
Instructors: 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.