|9/23||Orientation and computational laboratory introduction|
|9/28, 9/30||Biophysical foundations. Channel transport and membrane dynamics; Nernst equilibrium and Goldman-Hodgkin-Katz equation.||W1 Lecture|
|10/5, 10/7||Full and reduced single-compartment neural models. Hodgkin-Huxley, FitzHugh-Nagumo and Moris-Lecar equations.||W2 Lecture|
|10/12, 10/14||Nonlinear dynamics of neural firing. Null clines, stationary points, stability, bifurcation, limit cycles.||W3 Lecture|
|10/19, 10/21||Conductance based models of synaptic coupling between neurons. Fast and slow acting chemical synapses, gap junctions.||W4 Lecture|
|10/26, 10/28||Spike timing-dependent synaptic plasticity. Hebbian learning and principal component analysis. Mean-rate STDP model, correlation learning and homeostasis.||W5 Lecture|
|11/2, 11/4||Computational modeling and efficient emulation of large networks. Conductance-based integrate-and-fire models; time-domain and event-based emulators; neuromorphic systems.||W6 Lecture|
|11/9||Neurophysiology foundations, and brain connectivity. Making sense of the connectome data: causal dynamics from structural networks.||W7 Lecture|
|11/16, 11/18||Coherent collective neural dynamics. Brain waves and EEG.
Guest lecture by Scott Makeig
|11/23||Learning over extended time scales. Dopamine phasic prediction error for reward; temporal difference reinforcement learning.
Guest lecture by Terry Sejnowski
|11/30, 12/2||Project final presentations. All are welcome!||Fall 2016 Projects|