If you have a question or issue with MNE-Python, please include the following info:
Could you tell me, how to compute source space induced power in given frequency bands for each epoches separately?
If I use mne.minimum_norm.source_band_induced_power, then I receive averaged epoches, but I would like separated (just like when we use mne.minimum_norm.apply_inverse_epochs but for given frequency bands).
Thank you in advance.
this is not currently implemented. You could do it one epoch at a time in a list comprehension, something like:
result = [mne.minimum_norm.source_band_induced_power(
epochs[ix], inv, bands) for ix in range(len(epochs))]
Okey:) Thank you very much
Hello:) now I have another confusion with epoched data on source space:(
When I computed stc with mne.minimum_norm.source_band_induced_power and got data averaged by epochs, I morphed it on fsaverage and averaged between subjects, and plotted the result, the I got picture with clear localization as I expected (Fig. 1). But when I computed stc for each epochs (in cycle, like you advised), then averaged data between epochs, morphed on fsaverage, then averaged between subjects - I got signal without clear localization, it appears to be smeared all over the hemisphere (although it is in that hemisphere and while expected) - Fig.2.
So I confused - I did something wrong with averaging stc for epochs, or can it be expected that the sources obtained from individual epochs may not be as clearly localized as those obtained from averaged data (since the inverse problem is solved here, and the signal from a separate epoch is noisier)?
I will be very thankfull for any hints, or or maybe there was a similar experience.
