.. _codex_fmri_2018_TaylorEtal: **Taylor et al. (2018).** *FMRI processing with AFNI: Some comments and corrections ...* ****************************************************************************************** .. contents:: :local: .. highlight:: Tcsh Introduction ============ Here we present commands used in the following paper: * | Taylor PA, Chen G, Glen DR, Rajendra JK, Reynolds RC, Cox RW (2018). FMRI processing with AFNI: Some comments and corrections on 'Exploring the Impact of Analysis Software on Task fMRI Results'. bioRxiv 308643; doi:10.1101/308643 | ``_ **Abstract:** A recent study posted on bioRxiv by Bowring, Maumet and Nichols aimed to compare results of FMRI data that had been processed with three commonly used software packages (AFNI, FSL and SPM). Their stated purpose was to use “default” settings of each software’s pipeline for task-based FMRI, and then to quantify overlaps in final clustering results and to measure similarity/dissimilarity in the final outcomes of packages. While in theory the setup sounds simple (implement each package’s defaults and compare results), practical realities make this difficult. For example, different softwares would recommend different spatial resolutions of the final data, but for the sake of comparisons, the same value must be used across all. Moreover, we would say that AFNI does not have an explicit default pipeline available: a wide diversity of datasets and study designs are acquired across the neuroimaging community, often requiring bespoke tailoring of basic processing rather than a “one-size-fits-all” pipeline. However, we do have strong recommendations for certain steps, and we are also aware that the choice of a given step might place requirements on other processing steps. Given the very clear reporting of the AFNI pipeline used in Bowring et al. paper, we take this opportunity to comment on some of these aspects of processing with AFNI here, clarifying a few mistakes therein and also offering recommendations. We provide point-by-point considerations of using AFNI’s processing pipeline design tool at the individual level, afni_proc.py, along with supplementary programs; while specifically discussed in the context of the present usage, many of these choices may serve as useful starting points for broader processing. It is our intention/hope that the user should examine data quality at every step, and we demonstrate how this is facilitated in AFNI, as well. **Study keywords:** task-block, EPI, MPRAGE, human, control, adult, MNI space, nonlinear align **Main programs:** ``afni_proc.py``, ``3dmask_tool``, ``recon-all`` (FS), ``@SUMA_Make_Spec_FS`` Download scripts ================ To download, either: * \.\.\. click the link(s) in the following table (perhaps Rightclick -> "Save Link As..."): .. list-table:: :header-rows: 0 * - |s01| - BMN-AFNI processing with ``afni_proc.py`` * - |s02| - NIMH-AFNI processing: skullstripping and alignment to standard space (via ``@SSwarper``) * - |s03| - NIMH-AFNI processing with ``afni_proc.py`` * - |s04| - NIMH-AFNI group level processing: ``3dMEMA``, ``3dClustSim``, clusterizing * \.\.\. or copy+paste into a terminal:: curl -O https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/media/2018_TaylorEtal/s.bmn_subject_level_02_ap.tcsh curl -O https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/media/2018_TaylorEtal/s.nimh_subject_level_01_qwarp.tcsh curl -O https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/media/2018_TaylorEtal/s.nimh_subject_level_02_ap.tcsh curl -O https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/media/2018_TaylorEtal/s.nimh_group_level_02_mema.tcsh View scripts ============ These scripts describe different approaches for processing FMRI data with AFNI. Please read the comments at the tops of the scripts carefully, as well as the bioRxiv papers associated with each, in order to understand the steps. These scripts were run on the NIH's Biowulf HPC cluster, hence some of the variables like ``$SLURM_CPUS_PER_TASK``, ``$SLURM_JOBID``, etc. ``s.bmn_subject_level_02_ap.tcsh`` ----------------------------------------- **Comment:** Several aspects of this particular script's command would *not* be recommended for processing (e.g., the nonlinear alignment program; the selection of volreg reference, and more). Please see the main paper for further details. .. literalinclude:: /codex/fmri/media/2018_TaylorEtal/s.bmn_subject_level_02_ap.tcsh :linenos: Script: ``s.nimh_subject_level_01_qwarp.tcsh`` ----------------------------------------------- **Comment:** ``@SSwarper`` syntax has changed a lot since these days. .. literalinclude:: /codex/fmri/media/2018_TaylorEtal/s.nimh_subject_level_01_qwarp.tcsh :linenos: Script: ``s.nimh_subject_level_02_ap.tcsh`` ----------------------------------------------- .. literalinclude:: /codex/fmri/media/2018_TaylorEtal/s.nimh_subject_level_02_ap.tcsh :linenos: Script: ``s.nimh_group_level_02_mema.tcsh`` ----------------------------------------------- **Comment:** Instead of using ``3dclust`` here, the more modern and convenient ``3dClusterize`` would now be recommended. .. literalinclude:: /codex/fmri/media/2018_TaylorEtal/s.nimh_group_level_02_mema.tcsh :linenos: .. aliases for scripts, so above is easier to read .. |s01| replace:: :download:`s.bmn_subject_level_02_ap.tcsh ` .. |s02| replace:: :download:`s.nimh_subject_level_01_qwarp.tcsh ` .. |s03| replace:: :download:`s.nimh_subject_level_02_ap.tcsh ` .. |s04| replace:: :download:`s.nimh_group_level_02_mema.tcsh `