Dear MNE community,
Is it possible to estimate the source of brain activity of a contrast between two different sessions?
If I were to estimate src for data originated in just one session, I know I’d have to compute the noise covariance and the inverse operator. However, the function ‘mne.compute_covariance’ only accepts epochs as input and a contrast between two sessions would always be evoked (I guess).
Can I compute the noise covariance using the epochs of just one of the sessions and then apply it to the inverse operator? Or should I compute the noise covariance for each session separately and then somehow subtract one from another?
epochs_session_1 = epochs_session_1['Hit'] epochs_session _2 = epochs_session_2['Hit_2'] contrast = mne.combine_evoked(epochs_session _1.average(), epochs_session _2.average() , weights=[1, -1])
noise_cov = mne.compute_covariance(#What should I pass here as input?, tmax=0., method=['shrunk', 'empirical'], rank='info', n_jobs=8)
If I was not clear, I would be happy to explain further details.
MNE-Python version: 0.22.0
operating system: Ubuntu 20.04.2 LTS