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