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Textbook: Theoretical
Neuroscience: Computational and Mathematical Modeling of Neural
Systems by Peter Dayan and Larry Abbott, MIT Press.
We'll be covering selected topics from the textbook, based on the composition and interests of the class. We will also have guest lectures on some of these topics from experts here at UW. Here's a tentative list of topics:
- Basic Neurobiology
- Neural Encoding: Spikes, Firing Rates, and Receptive Fields (Chapters 1-2)
- Neural Decoding and Population Codes (Chapter 3)
- Information Theory (Chapter 4)
- Single Neurons: Integrate-and-Fire and Compartmental (Chapters 5-6)
- Network Models: Feedforward and Recurrent Networks (Chapter 7)
- Synaptic Plasticity and Learning (Chapters 8-9)
Many but not necessarily all of these topics will be covered (as time
permits). Here's the tentative schedule (guest lecture dates subject to change!):
| Date |
Topic |
Reading |
Presenter |
| March 31 |
Introduction and Basic Neurobiology |
Lecture slides |
Raj |
| April 2 |
Neural Encoding:
Spike trains, firing rates, receptive fields, spike train statistics, reverse correlation |
Chaps. 1 and 2 |
Adrienne |
| April 7 |
Functional Models of Neural Computation |
Chap. 2 |
Adrienne |
| April 9 |
Biophysical modeling of single neurons and synapses |
Chap. 5 |
Adrienne |
| April 14 |
Dynamics of single neurons |
Chap. 6 |
Mike Famulare (guest lecturer) |
| April 16 |
Quantifying Spike-Timing Precision (Guest Lecture) |
Lecture slides |
Fred Rieke (PBIO) |
| April 21 |
Dynamics of Neural Populations (Guest Lecture) |
Lecture slides |
Eric Shea-Brown (AMATH) |
| April 23 |
Dendritic Computation |
Chap. 6 |
Adrienne |
| April 28 |
Information Theory and Neural Coding |
Chap. 4 |
Adrienne |
| April 30 |
Neural Decoding, Signal Detection Theory, and Bayesian Inference |
Chap. 3 |
Adrienne |
| May 5 |
Network Models |
Chap. 7 |
Raj |
| May 7 |
Recurrent Networks |
Chap. 7 |
Raj |
| May 12 |
Learning Networks |
Chap. 8 |
Raj |
| May 14 |
Motor Control and Learning I (Guest Lecture) |
Lecture slides |
Emo Todorov (CSE/AMATH) |
| May 19 |
Motor Control and Learning II (Guest Lecture) |
Lecture slides |
Emo Todorov (CSE/AMATH) |
| May 21 |
Unsupervised Learning |
Chap. 10 |
Raj |
| May 26 |
Supervised Learning |
Lecture slides |
Raj |
| May 28 |
Guest Lecture: Decision making and sequential analysis |
Lecture slides |
Mike Shadlen (PBIO) |
| June 2 |
Reinforcement Learning |
Chap. 9 |
Raj |
| June 4 |
Course Summary |
Lecture slides |
Adrienne & Raj |
| June 8, Monday, 10:30-12:20pm |
Group project presentations (written reports due June 10 midnight) |
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Student teams |
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