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fMRI Acquisition and Analysis Course
May 6 - May 8
The course faculty include:
Kent Kiehl (Mind Research Network & University of New Mexico)
Vince Calhoun (Georgia State University, Georgia Institute of Technology and Emory University)
Tor Wager (Dartmouth College, Department of Biological & Brain Sciences)
The course is designed for fMRI researchers who range from beginning to intermediate skill levels. It will provide those who are just getting started with fMRI a comprehensive set of tools and software to get started with your own studies, and those who are more advanced will benefit from custom code and supplements to standard analyses developed by the instructors. We cover Statistical Parametric Mapping (SPM12), independent component analyses (ICA) of fMRI data, mediation analysis of fMRI, and statistical nonparametric mapping (SnPM). We provide comprehensive coverage of all aspects of experimental design, image acquisition, image preprocessing, and analysis using the general linear model and ICA.
The course is unique in that it pairs interactive lectures with hands-on demonstrations and work-through sessions. Each student works on their own laptop. Software will be installed on each student’s laptop during the beginning of the course, including Matlab (a trial version), SPM12, the Group ICA of fMRI Toolbox (GIFT), and related SPM toolboxes, including statistical nonparametric mapping (SnPM) and the multi-level mediation fMRI toolbox (M3). In addition, alongside the lectures, participants will be trained to analyze example fMRI data on their laptops using these tools. The course will be small and interactive, with many opportunities to work closely with the faculty. Registration will be on a first-come, first-served basis; we apologize in advance if we cannot accommodate all who wish to attend, but we will admit as many people as possible given the interactive nature of the course.
Dates and Time:
May 6-8, 2020
Georgia State University
55 Park PL NE, 18th Floor
Atlanta, GA 30303
Register as trainee ($895) – this category includes undergraduate and graduate students, post-doctoral fellows or trainees in a post-graduate training period prior to graduate school.