Skip to content

AFNI 3D Smoothness Estimation (3dFWHMx)

Library: AFNI | Docker Image: brainlife/afni

Function

Estimates spatial smoothness of data using the autocorrelation function (ACF) model.

Modality: Residual 4D NIfTI/AFNI from GLM analysis plus brain mask.

Typical Use: Getting smoothness estimates for 3dClustSim.

Key Parameters

-input (residuals), -mask (brain mask), -acf (output ACF parameters), -detrend (detrend order)

Key Points

Run on residuals (not original data). ACF model accounts for non-Gaussian spatial structure. Output feeds into 3dClustSim.

Inputs

Name Type Required Label Flag
input File Yes Input dataset -input
mask File No Use only nonzero voxels in mask -mask
automask boolean No Generate mask automatically from input -automask
demed boolean No Subtract median of each voxel time series -demed
unif boolean No Normalize voxel time series to same MAD -unif
detrend int No Remove polynomial trends up to order q -detrend
detprefix string No Save detrended dataset with prefix -detprefix
geom boolean No Compute geometric mean of FWHM (default) -geom
arith boolean No Compute arithmetic mean of FWHM -arith
combine boolean No Combine measurements along each axis -combine
acf string No Compute ACF fit (output a b c parameters) -acf
ACF string No Same as -acf but with comment lines -ACF
out string Yes Output filename for FWHM results -out
compat boolean No Compatibility mode with older 3dFWHM -compat
difMAD boolean No Use first/second neighbor differences with MAD -2difMAD

Accepted Input Extensions

  • input: .nii, .nii.gz, +orig.HEAD, +orig.BRIK, +tlrc.HEAD, +tlrc.BRIK
  • mask: .nii, .nii.gz, +orig.HEAD, +orig.BRIK, +tlrc.HEAD, +tlrc.BRIK

Outputs

Name Type Glob Pattern
fwhm_output File $(inputs.out)
acf_output File $(inputs.acf)
detrended File $(inputs.detprefix)+orig.*, $(inputs.detprefix).nii*
log File 3dFWHMx.log

Output Extensions

  • fwhm_output: .1D
  • acf_output: .1D
  • detrended: +orig.HEAD, +orig.BRIK, .nii, .nii.gz

Docker Tags

Available versions: latest, 16.3.0

Categories

  • Functional MRI > AFNI > Multiple Comparisons

Documentation

Official Documentation