Data covariance for source reconstruction of resting state EEG with Beamformer

Greetings BST Community,

Thus far in my work with Brainstorm and resting state EEG, I have been conducting source reconstruction with the MN method, which requires just a noise covariance (which I've been using the identity matrix for).

I am currently interested in how my metrics of interest (e.g., functional connectivity) may vary based on the source reconstruction method. I would thus like to also conduct source reconstruction of my resting state EEG with the Beamformer method.

I was hoping for some clarity around how to calculate the data covariance in the context of resting state EEG. In the data covariance page (, it states that for spontaneous data, to use the full time window.

In the case of resting state EEG where there is no stimulus, how should I go about specifying the "baseline" and "data" options? For example, if I have 30 seconds of data, I'm assuming "data" would be 0-30 seconds, but what would the baseline values be in this case?

EDIT - I think I may have misunderstood. Im my case, would I just select "data covariance", and the data covariance would be calculated based on the time window provided in "Data", and no need to specify the "Baseline" window?

Thank you,

Correct, the data covariance matrix will be computed with recordings in the Data time window.
The Baseline time window (in the GUI) is used only to DC correction (its mean will be removed from the recordings in the Data time window). In spontaneous recordings the same time window can be used for Baseline and Data time windows, resulting in a data covariance matrix computed with the AC recordings in that time window.

Note, although the noise covariance matrix is not used in estimating sources with the beamforming method, it is necessary to compute it to access to the Compute sources options:

EDIT: Added links

Thank you Raymundo!