Introduction to Computational Neuroscience

Calendar

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