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