With mne_volume_source_space I got a model with 6 discrete sources, 4 in
deep brain structures (brain stem) and 2 at the cortex. After getting the
forward solution and the inverse operator I was able to find the estimates
for these 6 sources but those at the cortex seem to be two orders of
magnitude smaller, which is not what I was expecting to get.
My question is: when MNE calculates the forward solution and the inverse
operator, does it take into account how deep are the dipoles? I am
wondering if somehow the gain in the G matrix (fwd.sol.data) or the noise
covariance matrix (inv.noise_cov.data) is smaller for the cortical dipoles
and therefore that is why I am seeing this differences in magnitude. Any
idea?
Thank you very much in advance for any help regarding this issue.
Sincerely,
The deeper dipoles are not weighted any differently from the cortical
ones.
The difference in magnitude is because on the cortex the estimates
have a chance (and will) spread out thus creating a weak distributed
source in MNE whereas there are only few brain stem dipoles have to
account for the data and will, therefore, be stronger. How to best
deal with this is subject to further investigation.
I understand that is the case when using several dipoles at the cortex and
a few at deeper structures but in my case the model has only 2 dipoles in
the cortex and four at the brain stem. Will it give me such results
regardless the number of dipoles and its locations?
Also, is it possible to find a way to scale the estimates at the cortex to
be able to compare them with the ones at deeper structures?