Skip to content

AFNI 3D Seed-Based Correlation (3dTcorr1D)

Library: AFNI | Docker Image: brainlife/afni

Function

Computes voxelwise correlation between a 4D dataset and one or more 1D seed time series.

Modality: 4D fMRI NIfTI/AFNI time series plus 1D seed time series file.

Typical Use: Seed-based functional connectivity analysis.

Key Parameters

-prefix (output), <4D_dataset> <1D_seed_timeseries>

Key Points

Simple seed-based correlation. Extract seed time series first (e.g., with 3dmaskave).

Inputs

Name Type Required Label Flag
xset File Yes Input 3D+time dataset
y1D File Yes 1D reference time series file
prefix string Yes Output dataset prefix -prefix
pearson boolean No Pearson product moment correlation (default) -pearson
spearman boolean No Spearman rank correlation -spearman
quadrant boolean No Quadrant correlation coefficient -quadrant
ktaub boolean No Kendall tau_b coefficient -ktaub
dot boolean No Calculate dot product instead of correlation -dot
Fisher boolean No Apply Fisher (arctanh) transformation -Fisher
mask File No Only process voxels nonzero in mask -mask
float boolean No Save results in float format (default) -float
short boolean No Save results in scaled short format -short

Accepted Input Extensions

  • xset: .nii, .nii.gz, +orig.HEAD, +orig.BRIK, +tlrc.HEAD, +tlrc.BRIK
  • y1D: .1D, .txt
  • mask: .nii, .nii.gz, +orig.HEAD, +orig.BRIK, +tlrc.HEAD, +tlrc.BRIK

Outputs

Name Type Glob Pattern
correlation File $(inputs.prefix)+orig.HEAD, $(inputs.prefix)+tlrc.HEAD
log File $(inputs.prefix).log

Output Extensions

  • correlation: +orig.HEAD, +orig.BRIK, +tlrc.HEAD, +tlrc.BRIK

Docker Tags

Available versions: latest, 16.3.0

Categories

  • Functional MRI > AFNI > Connectivity

Documentation

Official Documentation