In previous posts I’ve covered how to use AFNI to run GLMs on your data to find task-related activations.  But there are a host of other statistics that you can run on the brain outside of the GLM!  And this is where AFNI really shines in terms of having a diverse set of tools, yet […]

I previously reviewed a series of DICOM to NIFTI converters.  The entire purpose of this post is to state how important it is to check the orientation of the images coming out of any DICOM to NIFTI converter.  The example today illustrates an incorrect flip in dcm2nii, but I want to stress that this happens […]

Often when creating a mask to use with 3dROIstats, 3dmaskave, or 3dmaskdump, we will create a mask at a higher resolution than our functional runs, detailed here.  One of the reasons the mask is created at a higher resolution is that we base the anatomical masks on either 1) the high-resolution anatomical or 2) the […]

I receive a lot of questions about how to setup the basic analyses in AFNI.  Previously I detailed using uber_subject.py, the AFNI graphical user interface to afni_proc.py which really does all of the hard work under the hood.  Today I’m going to briefly review the common options in afni_proc.py and why I use them.  You […]

I could say a lot about proper simulation of fMRI experiments.  Basically it’s important to measure the efficiency of your design before an experiment (see here).  If you wanted to perform the calculations yourself, MATLAB/Python/Octave are all options and the process is “fairly simple”. Xmat = [design_matrix’ * design_matrix]; main_effects(ct) = [ contrast’ * (Xmat^-1) […]