Hello AFNI expert,

I am trying to interpret the quality check of the output of afni_proc.py in order to see if one or multiple metrics could help me to understand the quality of my results in resting-state fMRI in dogs. I basically tested 4 sequences, 1 SE EPI and 3 GE EPI. I co-registrate all the BOLD to a template and performed a seed base analysis.
Then, it appeared that the SE EPI gave me the "best" DMN statistical map (this is very subjective but I have got strong correlations to parietal and temporal areas that I do not have with the other sequences). For this reason, I am trying to understand if some parameters of the quality check could help me to understand what happened.
The motion has been checked and the lowest for the SE EPI and one GE EPI
The SE EPI got the lowest TSNR (28) and the others are around 40.
The grayplot seems way more homogenous for the SE EPI even if I compare it with the GE EPI sequence with less motion.
So that is probably the beginning of an explanation: less thermal noise or non explained noise?
[pubmed.ncbi.nlm.nih.gov]
Then, the most important difference is probably on the global correlation (GCOR).
SE EPI: 0.00862326
GE EPI, all around 0.2
can I interpret this difference?
on the corr_brain I have got a more scattered statistical map for the SE EPI when for some of the GE I got some aggregated voxels.
Are there any other metrics that I might want to look at?
I had a deep look at [afni.nimh.nih.gov] but I am still struggling to know which metrics should be used for my purposes and how to interpret them.
If you have any teaching documentation available, like the nice PDF that you produced for afni_proc.py don't hesitate to copy the link.
Of course, it is preliminary work and I would need statistics to fully validate any interpretations.
Thank you!
Clément