rs-fMRI preproc example
This example showcases a preprocessing pipeline for resting state fMRI (rs-fMRI) data, which loads a functional MRI file, applies slice time correction slice-time corrected, motion-corrected, regresses out the first two principal components within a noise ROI based on the 2% highest variance voxels (also known as tCompCor), applies a high-pass filter, and writes the preprocessed file to disk.
This pipeline is a reconstruction of the rs-fMRI pipeline from the Nipype website.
Check out the Porcupine-generated Python-script, Porcupine-pipeline, and associated Dockerfile in our Github repository or download the files directly below.