Courses:

Introduction to Computational Neuroscience >> Content Detail



Calendar / Schedule



Calendar

Lec #TOPICSKEY DATES
1Introduction

Examples of Neural Coding, Simple Linear Regression
2Convolution 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
3Convolution and Correlation 2

Spike-triggered Average

Wiener-Hopf Equations and White Noise Analysis
4Visual 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
5Visual Receptive Fields 2Assignment 2 due
Optional Lecture 3

Markov Processes
6Operant Matching 1
7Operant Matching 2Assignment 3 due
8Games 1
Optional Lecture 4

Linear Stability Analysis
9Games 2
10Project Meeting 1

Discussion of Topics, Choice of Projects, Work Begins
11Project Meeting 2Assignment 4 due
12Project Meeting 3
13Project Meeting 4
14Project Presentations 1
15Project Presentations 2
16Ion Channels, Nernst Equation, Passive Electrical Properties of Neurons
17The Action Potential, Hodgkin-Huxley Model 1
18Hodgkin-Huxley Model 2Assignment 5 due
19A-type Potassium Channels, Calcium-Dependent Potassium Channels
20SynapsesAssignment 6 due
Optional Lecture 5

Numerical Methods for Differential Equations
21Associative Memory 1
22Associative Memory 2Assignment 7 due
23Decisionmaking
24Projects
25Projects (cont.)
26Review
Final Exam

 








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