3 credits
Spring 2025 Lecture
Introduces students to the design of fMRI experiments and fMRI data analysis. Covered topics include an introduction to MR physics, block designs, rapid-event related designs, data preprocessing, and standard analyses using the general linear model. Advanced analysis techniques such as functional connectivity and multivariate pattern analysis and common pitfalls in design and analysis will also be covered. Prerequisites: Required: Basic knowledge of inferential statistics. Recommended: Familiarity with the general linear mode (GLM) and signal processing. Permission of department required.
Learning Outcomes1Understand how to design fMRI experiments.
2Perform fMRI analysis.
3Interpret the results of fMRI data analysis.
4Understand and avoid pitfalls related to fMRI data analysis.
Restrictions
Attachments
made by Purdue students.