AFNI Overview

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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.

Start to Finish Analysis with AFNI

• 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