14. Codex: AFNI Code Examples from publications

Below is an archive of “larger” AFNI commands that have been used in published work. We thank the authors who have kindly agreed to put their AFNI processing commands and/or scripts onto the interweb for public reference and use. These take the guess work out of translating a paper’s Methods section into a command and provide a good starting point for building your own scripts with AFNI.

Scripts and commands may be provided in simplified/basic form. One can also expect that file names or any other identifying information has been removed, relabelled, recoded, etc. We will try to make such instances obvious.

As the field develops, preferred processing steps will surely change over time. We will try to note these cases and their rationales when possible, but please reach out to discuss any possible improvements or modernizations.

We are always (well, usually) happy to answer questions via the AFNI Message Board, and hopefully these scripts further the discussion.

• 14.1. Overview
  • 14.1.1. Introduction
  • 14.1.2. Program names and keywords for searching
• 14.2. FMRI Codex
  • 14.2.1. Reynolds et al. (2024). Processing, evaluating and understanding FMRI data with afni_proc.py
  • 14.2.2. Beynel et al. (2024). Lessons learned from an fMRI-guided rTMS study …
  • 14.2.3. Taylor et al. (2024). A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth …
  • 14.2.4. Reynolds et al. (2023). Quality control practices in FMRI analysis: Philosophy, methods …
  • 14.2.5. Chen et al. (2023). BOLD response is more than just magnitude: improving detection …
  • 14.2.6. Taylor et al. (2023). Highlight Results, Don’t Hide Them: Enhance interpretation, …
  • 14.2.7. Steinhauser et al. (2023). Reduced vmPFC-insula functional connectivity in generalized …
  • 14.2.8. Chen et al. (2022). Hyperbolic trade-off: The importance of balancing trial …
  • 14.2.9. Atlas et al. (2022). Instructions and experiential learning have similar …
  • 14.2.10. Yang et al. (2021). Different activation signatures in the primary sensorimotor …
  • 14.2.11. Chen et al. (2018b). Handling Multiplicity in Neuroimaging Through Bayesian …
  • 14.2.12. Chen et al. (2018a). A tail of two sides: Artificially doubled false positive …
  • 14.2.13. Taylor et al. (2018). FMRI processing with AFNI: Some comments and corrections …
  • 14.2.14. Chen et al. (2016). Untangling the Relatedness among Correlations, Part II: …