Dear MNE community,

I want to perform a **cluster permutation** test comparing time-frequency (**morlet waves**) **EEG** data from 40 subjects performing a task in **two different sessions** and then visualize the significant clusters.

However, **I have not collected individual T1 images** from the subjects, thus I want to do the source estimation using the ‘**fsaverage**’ model.

For doing the **source estimation for just one subject** I have to perform the following steps:

- Coregister ‘fsavarage’ with my subjects’ contrasts (epoch_session_1, epoch_session_2)
- Compute the source space
- Compute BEM solution
- Compute the forward model
- Calculate the noise covariance matrix
- Create and apply the inverse operator
- Compute the adjacency matrix

But if I have **40 subjects**, should I perform source estimation (all steps above) for all my 40 subjects individually?

Or can I do it **only once** after concatenating epochs (or evokeds???) of all 40 subjects?

I’d be happy to explain further details and thankful for any feedback

Best regards,

Bruno

- MNE-Python version: 0.22.0
- operating system: * Ubuntu 20.04.2 LTS