Dear experts,
I have around 120 subjects with pre and post fMRIs that have been processed in FSL. Given the number of subjects and heterogeneity of the subjects there is quite a bit of ventromedial dropout that is evident in the fMRI scans and in the registration page of FSL evident by the “Sum of all input masks after transformation to standard space”
Please see attached image*
https://i.imgur.com/0Td9oNH.png
There are two solutions that I have thought about to solve the issue
1. Calculate the signal to noise ratio (SNR) of ROIs in the problematic areas and exclude subjects with SNRs bellow 90 or the lowest 10 percent.
2. Identify a peak point or ROI corresponding to the VMPFC as my area of interest and checking to see if the subjects MNI registered fMRI mask is included in the mask and exclude those who mask do not overlap with the ROI.
Which of above would be acceptable to QC the data or exclude subjects for analysis. My understanding of FSL feat is that it looks at masksum.nii.gz of all subjects (area in yellow) to perform statistical analysis and given the poor signal in some subjects some areas that I am specifically interested in do not get included in the statistical analysis. Any advice or suggestions are greatly appreciated.
Thank you so much in advance,
Arsalan M
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