10-731 CALD
85-735 Psychology
Computational Analyses of Brain Imaging

Spring 2003

 

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.

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 

Instructors:  Marcel Just   (marcel.just@cmu.edu), Tom Mitchell   (tom.mitchell@cmu.edu)

Course Schedule and Handouts

Note this is a tentative schedule, subject to change.