4.1. FMRI examples (brief)¶
4.1.1. Overview¶
Publications are listed in reverse chronological order. Many thanks to the authors who have made their work available for general benefit.
Below are searchable tags and labels for each paper. This may help when searching for a paper with a given type of data or desired processing step.
Tag (study descriptors): |
Label (for searchability) |
---|---|
FMRI paradigm: |
task-block, task-event, resting, naturalistic, par-other |
FMRI dset: |
EPI, dual phase (AP-PA), fmri-other |
Anatomical dset: |
MPRAGE, T1w, T2w, T1map, T2map, FLAIR, FLASH, PD, SWI, Angio, none, anat-other |
Subject population: |
human, nonhuman primate, macaque, rat, simulation, pop-other |
Subject characteristic: |
patient, control, char-other |
Subject age: |
prenatal, newborn, infant, child, juvenile, adult, senior, age-other |
Template space: |
MNI, Talairach, Haskins-ped, native, sp-other |
Template align method: |
linear, nonlinear, al-other |
Tissue segmentation: |
3dSeg, FreeSurfer, seg-other |
Tissue regression: |
ANATICOR, fANATICOR, PCA, WM+Vent, reg-other |
4.1.2. Publications with example scripts¶
- 2016
Chen GC, Taylor PA, Shin Y-W, Reynolds RC, Cox RW (2016). Untangling the Relatedness among Correlations, Part II: Inter-Subject Correlation Group Analysis through Linear Mixed-Effects Modeling. Neuroimage 147:825-840.
Chen GC, Shin Y-W, Taylor PA, Glen DR, Reynolds RC, Israel RB, Cox RW (2016). Untangling the Relatedness among Correlations, Part I: Nonparametric Approaches to Inter-Subject Correlation Analysis at the Group Level. Neuroimage 142:248-259. Corrigendum
See also
- tags
naturalistic, EPI, MPRAGE, human, control, adult, Talairach, nonlinear, FreeSurfer, fANATICOR
FreeSurfer segmentation;
@SUMA_Make_Spec_FS
; tissue selectionafni_proc.py
command
- 2018
Taylor PA, Chen GC, 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”
See also
- tags
task-block, EPI, MPRAGE, human, control, adult, MNI, nonlinear,
BMN-AFNI processing with afni_proc.py
NIMH-AFNI processing: skullstripping and alignment to standard space (via @SSwarper)
NIMH-AFNI processing with afni_proc.py
NIMH-AFNI group level processing: 3dMEMA, 3dClustSim, clusterizing
Chen GC, Cox RW, Glen DR, Rajendra JK, Reynolds RC, Taylor PA (2018). A tail of two sides: Artificially doubled false positive rates in neuroimaging due to the sidedness choice with t-tests
See also
- tags
task-block, EPI, MPRAGE, human, control, adult, MNI, nonlinear,
An example of group level analyses with two-tailed testing (using 3dMEMA, 3dClustSim and 3dClusterize, among others)
Chen GC, Xiao Y, Taylor PA, Riggins T, Geng F, Redcay E, Cox RW (2018). Handling Multiplicity in Neuroimaging through Bayesian Lenses with Hierarchical Modeling
See also
- tags
task-block, EPI, MPRAGE, human, adult
An example of group level analysis with the “Bayesian multilevel” (BML) approach.
The data table of subject information input into the BML analysis. See the associated paper for full description and generation.