AFNI

AFNI stands for Analysis of Functional NeuroImages, a software package for processing, analyzing, and visualizing functional MRI data. It was developed at the Medical College of Wisconsin and has been maintained since the 1990s. The package includes a set of command-line programs and a graphical user interface and supports 3D+time datasets. AFNI provides preprocessing tools for slice timing, motion correction, normalization, brain extraction, and other steps; for statistical analysis it offers a General Linear Model implementation via 3dDeconvolve and related programs; and for visualization it includes the AFNI GUI and SUMA for surface-based visualization.

AFNI data formats include the native BRIK/HEAD format as well as support for NIfTI-1, facilitating data exchange with other neuroimaging tools. Workflows are scriptable, enabling automated pipelines through shell scripts or AFNI's program options. Common utilities include 3dvolreg (motion correction), 3dcalc (voxelwise calculations), 3dmaskdump, 3dROIstats, 3dttest, and 3dLME for mixed-effects analyses.

AFNI is cross-platform, mainly used on Unix-like systems and macOS; Windows users can run it via Cygwin or Windows Subsystem for Linux or use available native builds. It is widely used in academic neuroimaging research and has an active user community, extensive documentation, and online forums. AFNI's companion project SUMA provides surface-based visualization and integration with cortical models.