PSYCH 650 / CS 591.06 - Spring 1999 - Course Summary

Application of Signal Processing Tools to Brain Imaging Data

Time: Thursdays, 5:00-7:30, room TBA (first class 21-Jan-1999 meets 162 Logan Hall)
Instructors: Prof Akaysha Tang, Prof Barak Pearlmutter


Psych650 emphasizes the analysis and interpretation of functional brain imaging data. This data oriented hands-on course has five basic components:
  1. Physics, experimental protocol, and statistical analysis for EEG, MEG and fMRI.

  2. General mathematical tools and programming environment for analysis of brain imaging data.

  3. Theory of source separation and programming tools for source separation.

  4. Application of source separation to EEG, MEG, and fMRI data.

  5. Supervised and collaborative research project development.
Students will be given book chapters and original research papers to read before most of the lectures, and are expected to spend time outside class to familiarize themselves with the tools and data sets introduced in class, and to do a class project.


Jan 21 intro & overview of brain imaging techniques & data
28 Fourier Analysis
Feb 4 Matlab - signal processing (Fourier analysis)
11 EEG & MEG - physics, dipole methods
18 source separation - theory
25 source separation - tools (in Matlab)
Mar 4 EEG - classic literature, modern reaction time work
11 EEG - source separation & artifact removal, single trial analysis
+ project ideas
18 spring break
25 Matlab - graphics
Apr 1 MEG literature
8 project progress reports
15 CNS Conference Postmortum
22 fMRI - physics, experiments & statistics
29 fMRI - source separation
May 6 project presentations

Barak Pearlmutter <>