Description: With the growing flood of brain imaging data, computer
methods play an increasingly critical role in extracting knowledge from
experimental data, and in characterizing patterns of brain activity. This
course will survey computer methods for analyzing brain imaging data, ranging
from widely used software for signal processing and visualization (e.g.,
AFNI, Fiasco, Brain Voyager, SPM), to approaches that have just recently
seen growing use (e.g., Independent Components Analysis), to research on new
methods (e.g., machine learning approaches to decoding mental states), to
research on computational cognitive models (e.g., 4CAPS, ACT-R). We'll look
at the problems of computer analysis from the perspective of the scientific
questions that underlie cognitive neuroscience. The course work will consist
of presenting and learning from tutorial sessions on the methods, and
applying the methods in small projects.
Computational Analyses of Brain Imaging
Prerequisites: A background in both cognitive neuroscience
(particularly fMRI or PET) and in computational/quantitative methods (such as
intermediate statistics or machine learning) would be desirable, but a strong
background in only one of these approaches is acceptable.
Time: Wednesdays 7:00 pm - 9:45 pm
Location: Baker Hall 340 A
Tom Mitchell (firstname.lastname@example.org)
Course Schedule and Handouts
Note this is a tentative schedule, subject to change.
- Jan 15. Overview fMRI basics, sample of data analysis methods.
- Jan 22. Statistical Parametric Mapping (SPM) (part 1) Guest lecturer: Stuart Derbyshire
- Jan 29. SPM (part 2) Guest lecturer: Stuart Derbyshire
- Feb 5. fMRI Processing in FIASCO Guest lecturer: Bill Eddy, Prof
of Statistics, CMU
- Feb 12. Class project brainstorming
- Feb 19. Data analysis in CCBI. Guest Lecturer: Vladimir Cherkassky Powerpoint slides
- Feb 26. Marcel Just
- Mar 5. Machine learning methods. Tom Mitchell. Powerpoint slides part 1, part 2
- Mar 12. Cognitive modeling with fMRI: 4CAPS. Marcel Just.
- Mar 19. fMRI and studying conciousness. Lloyd paper , Ishai commentary
- Mar 26 Spring Break.
- Apr 2. Neural modeling and functional brain imaging. (required) Neural modeling and functional brain
imaging: an overview,
related paper) Neural modeling, functional brain imaging, and cognition,
- Apr 9. non-BOLD fMRI Guest lecturer: Seong-Gi Kim, Prof of Neurobiology, Univ. of Pittsburgh.
Required reading: Principles of Functional MRI
- Apr 16. Guest lecturer: Walter Schneider, Prof of Psychology, Univ. of Pittsburgh.
- Apr 23. Student presentations
- Apr 30. Student presentations