Hi Everyone
I am trying to do classification of rs-fMRI data, The problem is that I have several rs-fMRI data for each person and I have to choose one among them (supposing that they all passed pre-processing steps) but I don't know how. I looked at the data that is left over by uber_subject.py, And I saw TSNR, When I checked the data carefully I saw that usually
TSNR average, is correlated with
TRs censored That means when the number of censoed TRs goes up usually average TSNR goes up too. So I guessed that lower TSNR would be better, so I chose the data with the least TSNR, But my results are very bad, so I went back and chose the ones with the highest TSNR, now my results are much more better. How is that possible? How can a subject that lost lots of its TRs have higher TSNR and works better when it comes to functional analysis?
Edited 1 time(s). Last edit at 03/03/2017 02:24AM by heretic133.
