Here's a tentative list of topics (chapters refer to the Dayan and Abbott textbook):
Date |
Topic |
Reading |
Presenter |
March 29 |
Introduction and Basic Neurobiology |
Lecture slides |
Raj |
March 31 |
Neural Encoding: Spike trains, firing rates, receptive fields, reverse correlation |
Chaps. 1 and 2 |
Adrienne |
April 5 |
Functional Models of Neural Computation |
Chap. 2 |
Adrienne |
April 7 |
Neural Decoding, Signal Detection Theory, and Bayesian Inference |
Chap. 3 |
Adrienne |
April 12 |
Guest Lecture: Noisy Integration and Signal Detection |
Lecture slides |
Fred Rieke (PBIO) |
April 14 |
Information Theory and Neural Coding |
Chap. 4 |
Adrienne |
April 19 |
Biophysical Modeling of Single Neurons and Synapses |
Chap. 5 |
Adrienne |
April 21 |
Dendritic Computation |
Chap. 6 |
Adrienne |
April 26 |
Dynamics of Single Neurons |
Chap. 6 |
Adrienne |
April 28 |
Network Models |
Chap. 7 |
Raj |
May 3 |
Recurrent Networks |
Chap. 7 |
Raj |
May 5 |
Dynamics of Neural Populations (Guest Lecture) |
Lecture slides |
Eric Shea-Brown (AMATH) |
May 10 |
Learning Networks |
Chap. 8 |
Raj |
May 12 |
Unsupervised Learning |
Chap. 10 |
Raj |
May 17 |
Supervised Learning |
Lecture slides |
Raj |
May 19 |
Reinforcement Learning |
Chap. 9 |
Raj |
May 24 |
Motor Control and Learning I (Guest Lecture) |
Lecture slides |
Emo Todorov (CSE/AMATH) |
May 26 |
Motor Control and Learning II (Guest Lecture) |
Lecture slides |
Emo Todorov (CSE/AMATH) |
May 31 |
Decision Making (Guest Lecture) |
Lecture slides |
Mike Shadlen (PBIO) |
June 2 |
Course Summary |
Lecture slides |
Adrienne & Raj |
June 9, Thursday, 10:30-12:20pm |
Group project presentations (written reports due June 9 midnight) |
|
Student teams |