Dear all,
I have just noticed the new update with the Compute sources 2018 options. I am computing souces on a mixed surface/volume model and I have just read in the tutorials that the new interface can handle those, but I have not found any additional information about it. Can I already use the 2018 menu or should I keep using the 2009 one? Which are the new features of the 2018 update?
Thanks,
Natàlia
Hi Natàlia, the 2018 and 2009 should give nearly identical results, particularly for the mixed head model. The 2016 update by me did not include mixed head models, which I have fixed now. I would welcome your testing and confirming or noting any noticeable changes.
The 2016 update also changed the definition of the noise regularization parameter to be a fraction of the largest eigenvalue, but this was causing confusion with users who thought it should be the fraction of the average eigenvalue of the noise covariance matrix. Both the 2009 and the 2018 now use noise regularization parameter as the average of the eigenvalues, which is the same as the average of the diagonal values.
Because of these differences, we opted for now to leave all three versions up, so that users can adapt and test the new 2018 interface, which will ultimately become the default.
Hi John, Thank you for the fast reply.
I have been playing around a little bit with the different updates and I came up with some differences regarding the source localization. I am trying to analyse the activity in the brainstem and thalamus using a mixed head model, and I computed the sources using both the 2009 and the 2018 update.
When using the wMNE from the 2009 menu (First image), I find some activity in the brainstem (as expected). However, when computing the sources with the 2018 update using the minimum norm imaging method (second image), I don't see anything on the deepbrain structures and it seems that the activity tends to be located in the surface.
I think that I have applied the same parameters in both cases, although in the 2009 I am computing the sources using the wMNE. Could this be the difference? Which would be the equivalent in the 2018 menu?
BTW, the 2016 version keeps giving me error, saying that "BST_INVERSE > Mosher does not understand why we are passing multiple headmodels".
Many Thanks,
Natàlia.
@John_Mosher can help better. He’ll be back next week.
