Scripts related to the following paper:
Highlight Results, Don't Hide Them: Enhance interpretation, reduce
biases and improve reproducibility
by Paul A Taylor, Richard C Reynolds, Vince Calhoun, Javier
Gonzalez-Castillo, Daniel A Handwerker, Peter A Bandettini, Amanda F
Mejia, Gang Chen (2023)
Neuroimage 274:120138. doi: 10.1016/j.neuroimage.2023.120138
https://pubmed.ncbi.nlm.nih.gov/37116766/
The input data comes from the NARPS project (Botvinik-Nezer et al., 2020):
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771346/
This paper uses both the raw, unprocessed data as well as the
participating teams' results, which were uploaded to NeuroVault (see
the same paper for those details).
Essentially all scripts here use AFNI; one also uses FreeSurfer.
The scripts_biowulf directory contains the main processing scripts,
including:
- Checking the data
- Estimating nonlinear alignment to template space and skullstripping
with
@SSwarper - Full FMRI time series processing through regression modeling and QC
generation with
afni_proc.py - Group level modeling: both voxelwise (with cluster calcs) and
ROI-based (using
RBA, in particular)
... and more.
The scripts_suppl_proc_vox directory contains supplementary scripts
for making images of the above-processed data, mainly for figure
generation.
The scripts_suppl_proc_teams directory contains scripts for
processing the group-level results of the original participating Teams
in the NARPS project. Those public datasets were downloaded from
NeuroVault. The scripts make a lot of images and perform some simple
similarity analyses.