To get the cluster's time series, you have two options:
create a cluster, use the process Extract > Clusters time series, then compute what you need on the resulting file
Use a montage and the process "Standardize > Apply montage" to create a new signal in the files. Do not try to do any source modeling on the files you have modified in this way.
I have created a few clusters containing signals from different electrodes contacts (each cluster = one brain region, eg hippocampus, frontal lobe and fusiform gyrus). I would like to calculate the connectivity matrix between these clusters. Is that possible in BrainStorm?
I am not sure that I understand the method you described above with the "Standardize > Apply montage". How is that related to the clusters? Could you detail this part a bit further?
I'm not sure how an electrode can be attributed to the recording of the hippocampus.
You have to be careful with attribution of EEG electrode=brain region. EEG scalp potentials are very smooth, due to the skull and the diffusion of the currents in the head tissues. Some EEG features visible on most of the electrodes (eg. P300) can't be attributed to a single brain region.
I would like to calculate the connectivity matrix between these clusters. Is that possible in BrainStorm?
I forgot to precise, but I work on intracraniel EEG data. That's why I a able to attribute one electrode to one brain region.
It makes more sense, indeed.
However, in SEEG/ECOG, it might not be a good option to average the signals of different electrodes. Because each channel can contain different information, averaging them might lead to blur the meaningful information.
It could make sense to compute the measure of interest (PSD, connectivity, ...) for each channel individually, and then try to group the final measures by brain region.