Lec # | TOPICS | KEY DATES |
---|---|---|
1 | Introduction Examples of Neural Coding, Simple Linear Regression |
|
2 | Convolution and Correlation 1 Firing Rate |
|
Optional Lecture 1 Initializing and Using Vectors and Matrices in MATLAB®, Matrix Shortcuts, Plots in MATLAB®, Useful Commands Simple Statistics and Linear Regression |
||
3 | Convolution and Correlation 2 Spike-triggered Average Wiener-Hopf Equations and White Noise Analysis |
|
4 | Visual Receptive Fields 1 Basics of the Visual System, Center-surround Receptive Fields, Simple and Complex Cortical Cells |
Assignment 1 due |
Optional Lecture 2 Probability Theory |
||
5 | Visual Receptive Fields 2 | Assignment 2 due |
Optional Lecture 3 Markov Processes |
||
6 | Operant Matching 1 | |
7 | Operant Matching 2 | Assignment 3 due |
8 | Games 1 | |
Optional Lecture 4 Linear Stability Analysis |
||
9 | Games 2 | |
10 | Project Meeting 1 Discussion of Topics, Choice of Projects, Work Begins |
|
11 | Project Meeting 2 | Assignment 4 due |
12 | Project Meeting 3 | |
13 | Project Meeting 4 | |
14 | Project Presentations 1 | |
15 | Project Presentations 2 | |
16 | Ion Channels, Nernst Equation, Passive Electrical Properties of Neurons | |
17 | The Action Potential, Hodgkin-Huxley Model 1 | |
18 | Hodgkin-Huxley Model 2 | Assignment 5 due |
19 | A-type Potassium Channels, Calcium-Dependent Potassium Channels | |
20 | Synapses | Assignment 6 due |
Optional Lecture 5 Numerical Methods for Differential Equations |
||
21 | Associative Memory 1 | |
22 | Associative Memory 2 | Assignment 7 due |
23 | Decisionmaking | |
24 | Projects | |
25 | Projects (cont.) | |
26 | Review | |
Final Exam |