Hi,

I saw, in the tutorial, we need to calculate data covariance if we wanna use sLoreta. But, I found that, after I got noise covarance, I calculated sLoreta without data covariance successfully. Is this correct?

There is no need for a data covariance for sLORETA. It is only useful for the LCMV beamformer.

Where did you read this in the documentation?

Hi Francois,

I was having the same doubt. I confirm it to be written in the tutorial 22 at the "Measure [TODO]" paragraph.

Is that a typo?

Thank you,

Ramtin

I confirm that the sLORETA computation does not use any data covariance.

@John_Mosher @Sylvain

Could you please have a look at the sLORETA documentation and rephrase it so that it is less confusing for the readers?

Thanks a lot.

Ramtin

Hi,

@John_Mosher has updated Source Estimation tutorial (Tutorial 22) to help understand better the difference between "noise covariance" (used in dSPM) and "theoretical data covariance" (term used in Pascual-Marqui's publication). As correctly pointed out in this thread, sLORETA does not use the experimental data covariance. It does use the noise covariance which is added to the theoretical signal covariance to form the theoretical data covariance. Hope it is a little more clear now.

Please see: https://neuroimage.usc.edu/brainstorm/Tutorials/SourceEstimation