I am working with some resting-state EEG data and trying to find out what is the most sensible approach to compute sources. I was opting for sLORETA using (as suggested in the tutorial) identity matrix as noise covariance, obtaining very noisy signal at deeper sources.
As far as I understood, sLORETA standardizes the source data by the noise, which in this case would be the identity matrix. Is it then a sensible approach? Should I maybe compute the covariance matrix on long resting-state recordings (e.g. 40s) and choosing the diagonal at the source computation step in order to obtain a subject specific
Many thanks for your help