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 […]
Using afni_proc.py for fMRI analysis
https://blog.cogneurostats.com/2013/10/22/using-afni_proc-py-for-fmri-analysis/
Simulating fMRI Designs
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) […]
https://blog.cogneurostats.com/2013/10/10/simulating-fmri-designs/
Adjusting MRI Smoothness for Multi-Scanner Comparisons
Typically when we smooth (aka spatial filter) our fMRI data using a fixed kernel size. And as we know, the size of a smoothing kernel makes some difference in the final results (see below). This shows a group analysis map, the results are more shocking on single subject maps. The common misconception is that you […]
https://blog.cogneurostats.com/2013/10/07/smoothing-mri-images-in-afni/