Introduction to the nonlinear dynamics of neurons and simple neural systems through nonlinear dynamics,
bifurcation theory, and chaotic motions. The dynamics of single cells is considered at different levels of
abstraction, e.g., biophysical and "reduced" models for analysis of regularly spiking and bursting cells,
their dynamical properties, and their representation in phase space. The dynamics of synaptic plasticity is
studied based on relative timing of neural spikes. Advanced topics such as spatiotemporal dynamics of EEG
will be presented in guest lectures. Homework exercises and an in-class computational laboratory will
accompany the lectures, and students will work in groups on a final project. Requirements include in-class
presentation and submission of a final project report.
Projects will be drawn from a range of topics in computational modeling and analysis of dynamics in
biological and engineered neural systems, based on the research interests of the students. Interdisciplinary
approaches are highly recommended, such as projects involving VLSI design of dynamical neural systems
implemented in silicon circuits.
Lecture: Wednesday, 3:00p - 4:50p, PFBH 161
Computational Lab: Friday, 3:00p - 4:50p, PFBH 161
40%   Computational Labs and Homework