What is AFNI?
AFNI (Analysis of Functional NeuroImages) is a suite of programs designed to analyze fMRI data. Created in the mid-1990’s by Bob Cox, AFNI is now used by hundreds of imaging labs around the world.
The following tutorials will show you how to analyze a sample dataset with AFNI. You will begin by learning the fundamentals of fMRI preprocessing, and then proceed to create a model of your data with AFNI’s 3dDeconvolve command. We will finish by learning about different types of group analyses, and how to do region of interest (ROI) analyses.
- Introduction to AFNI
- AFNI Tutorial #1: Downloading the Data
- AFNI Tutorial #2: The Flanker Experiment
- AFNI Tutorial #3: Looking at the Data
- AFNI Tutorial #4: AFNI Commands and Preprocessing
- AFNI Tutorial #5: Statistics and Modeling
- AFNI Tutorial #6: Scripting
- AFNI Tutorial #7: Group Analysis
- AFNI Tutorial #8: ROI Analysis
- AFNI Tutorial #9: Surface-Based Analysis with SUMA
- Appendix A: Parametric Modulation in AFNI
- Appendix B: Analyzing Rat Data
- Appendix C: Highlighting Vs. Hiding Results
- Appendix D: Reporting Effect Sizes