Hi, EEG is already used for dynamic connectivity analysis and in my opinion it is much better tool for this (because of temporal resolution). The neuronal connectivity in EEG is also known for much longer than fMRI (however named differently, as coherence or DTF). There are few things that you have keep in mind to do this correctly:

1. You need high density EEG - at minimum 32 channels, recommended 64 and above

2. Very good data quality (i.e. high SNR).

3. There are a lot of papers suggesting that EEG connectivity analysis should be performed using source space and not sensor space. So first data has to be recomputed to source space.

I

think fieldtrip has some solution for EEG connectivity analysis if you need freeware tool. You might also check BESA Connectivity

https://youtu.be/Br2uh8l769E

PM me in case you need any more info about Besa Connectivity (I do not want to make advertisements here :)

You could feed the EEG data into the swLORETA computer program.

@ mateusz , @ Gonzalo

thanks a lot for your answers

Dynamic connectivity should be possible in EEG. But comparing it to fMRI is difficult to do on a general level. It all depends on what type of connectivity you want to investigate and why? You can do all sorts of funky connectivity analysis with EEG, but that dos not mean they make sense. The biggest problem in EEG is the spread of electric fields, which makes a lot of connectivity values spurious.

For a good overview of methods and issues in EEG connectivity I recommend this paper: https://www.frontiersin.org/articles/10.3389/fnsys.2015.00175/full

Hope it helps.