| Date | Topic | Lecture Materials |
|---|---|---|
| 9/27 | Orientation and computational laboratory introduction | |
| 9/30, 10/4 | Biophysical foundations. Channel transport and membrane dynamics; Nernst equilibrium and Goldman-Hodgkin-Katz equation. | W1 Lectures |
| 10/7, 10/11 | Full and reduced single-compartment neural models. Hodgkin-Huxley, FitzHugh-Nagumo and Moris-Lecar equations. | W2 Lectures |
| 10/14, 10/18 | Nonlinear dynamics of neural firing. Null clines, stationary points, stability, bifurcation, limit cycles. | W3 Lectures |
| 10/21, 10/25 | Conductance based models of synaptic coupling between neurons. Fast and slow acting chemical synapses, gap junctions. | W4 Lectures |
| 10/28, 11/1 | Spike timing-dependent synaptic plasticity. Hebbian learning and principal component analysis. Mean-rate STDP model, correlation learning and homeostasis. | W5 Lectures |
| 11/4, 11/8 | Computational modeling and efficient emulation of large networks. Conductance-based integrate-and-fire models; time-domain and event-based emulators; neuromorphic systems. | W6 Lectures |
| 11/15 | Subha Sivagnanam and Amit Majumdar: The Neuroscience Gateway -- Enabling large scale simulation and data processing in neuroscience | |
| 11/18 11/22 |
Tom Bartol: Monte Carlo modeling of molecular synaptic dynamics Terrence Sejnowski: Learning how to soar like a bird |
|
| 11/25 | Scott Makeig: Human cognitive event-related brain dynamics | |
| 12/2, 12/6 | Project final presentations. All are welcome! | Fall 2019 Projects |