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Neuroscience Graduate Program at UCSF
NS248 - Fall 2007
Neural and Behavioral Data Analysis
Course Director: Loren Frank
E-mail: loren@phy.ucsf.edu
Prerequisite: NS201A and NS201B or permission of the course director.
First Class: Wednesday, September 5, 2007
Classes are held on Wednesday and Friday morning from 9:00-11:00am in N-527, Parnassus
Attendance is expected (for those taking the course for credit)
Course Description:
This advanced course will provide an in-depth introduction to methods and techniques used for the analysis of neural and behavioral data. The following topics will be discussed: probability and probability distributions, descriptive statistics for gaussian and non-gaussian data, regression, auto and cross correlations, reverse correlation, information theory and likelihood based model building for both neural and behavioral data. The course will involve substantial programming in Matlab and previous Matlab experience is strongly recommended. Students will be expected to attend all of the lectures, complete the weekly problem sets and present solutions to the problem sets in the weekley discussion section. There will also be a final project.
Course Materials:
Materials are located here: http://phy.ucsf.edu/~loren/NS248
Course Schedule:
Date |
Time |
Location |
Lecturer |
Subject |
September |
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| Wed. Sep. 5 | 9-11am | N-527 | Katrin Schenk | Intro to Matlab - Optional |
| Fri. Sep. 7 | 9-11am | N-527 | Loren Frank | Lecture 1 - Probability |
| Wed. Sep. 12 | 9-11am | N-527 | Loren Frank | Lecture 1 - Problem set |
| Fri. Sep. 14 | 9-11am | N-527 | Katrin Schenk | Lecture 2 - Information Theory |
| Wed. Sep. 19 | 9-11am | N-527 | Katrin Schenk | Lecture 2 - Problem Set |
| Fri. Sep. 21 | 9-11am | N-527 | Loren Frank | Lecture 3 - Distributions |
| Wed. Sep. 26 | 9-11am | N-527 | Loren Frank | Lecture 3 - Problem Set |
| Fri. Sep. 28 | 9-11am | N-527 | Loren Frank | Lecture 4 - Descriptive Statistics |
October |
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| Wed. Oct. 3 | 9-11am | N-527 | Loren Frank | Lecture 4 - Problem Set |
| Fri. Oct. 5 | 9-11am | N-527 | Loren Frank | Lecture 5 - Regression and GLM |
| Wed. Oct. 10 | 9-11am | N-527 | Loren Frank | Lecture 5 - Problem Set |
| Fri. Oct. 12 | 9-11am | N-527 | Philip Sabes | Lecture 6 - Resampling |
| Wed. Oct. 17 | 9-11am | N-527 | Philip Sabes | Lecture 6 - Problem Set |
| Fri. Oct. 19 | 9-11am | N-527 | Loren Frank | Lecture 7 - Poisson Processes |
| Wed. Oct. 24 | 9-11am | N-527 | Loren Frank | Lecture 7 - Problem Set |
| Fri. Oct. 26 | 9-11am | N-527 | Loren Frank | Lecture 8 - Conditional Intensity |
| Wed. Oct. 31 | 9-11am | N-527 | Loren Frank | Lecture 8 - Problem Set |
November |
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| Fri. Nov. 2 | No Class - SFN | |||
| Wed. Nov. 7 | No Class - SFN | |||
| Fri. Nov. 9 | 9-11am | N-527 | Loren Frank | Lecture 9 - Maximum Likelihood |
| Wed. Nov. 14 | 9-11am | N-527 | Loren Frank | Lecture 9 Problem Set |
| Fri. Nov. 16 | 9-11am | N-527 | Loren Frank | Lecture 10 - Adaptive Estimation |
| Wed. Nov. 21 | Thanksgiving Holiday | No Class | ||
| Fri. Nov. 23 | Thanksgiving Holiday | No Class | ||
| Wed. Nov. 28 | 9-11am | N-527 | Loren Frank | Lecture 10 - Problem Set |
| Fri. Nov. 30 | 9-11am | N-527 | Loren Frank | Lecture 11 - Spike Train Correlations |
December |
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| Wed. Dec. 5 | 9-11am | N-527 | Loren Frank | Lecture 11 - Problem Set |
| Fri. Dec. 7 | 9-11am | N-527 | Students | Projects 1 |
| Wed. Dec. 12 | 9-11am | N-527 | Students | Projects 2 |
| Fri. Dec. 14 | 9-11am | N-527 | David Copenhagen | Evaluation |