Hi there,
I am testing different normalization methods on resting-state fMRI functional connectivity matrices to predict cognitive scores.
I found that instead of normalizing each feature across samples, normalizing each sample (i.e., each FC matrix within subject) works better.
Does anyone use this kind of normalization? or know any references using this kind of normalization?
Thanks!