Dear all,
I am working with data from an Elekta Neuromag system and I am not sure about using autossps. From the description of this tutorial https://neuroimage.usc.edu/brainstorm/Tutorials/TutMindNeuromag#Existing_SSP_projectors I understand that the autossps should rather not be used. But would it be an absolute NoGo, because after all the autossps were designed specifically for their own MEG system. Or is it a clear advantge to recalculate the SSPs? With the alternative to use tsss, as mentioned in the tutorial, I am myself cautious, because tsss, at least in my case, partly filters out important signal, such as the tremor frequency. I would be very happy about opinions about a proper handling of autossps or sources where I myself find more information.
Greetings,
Matthias
The tutorial section you pointed at contains all our recommendations regarding these autossp projectors.
https://neuroimage.usc.edu/brainstorm/Tutorials/TutMindNeuromag#Existing_SSP_projectors
Maybe the MNE-Python team has different recommendations to share?
@Alexandre
If you want to know whether you can use these SSPs in your analysis in Brainstorm despite our recommendation to disable them, maybe you could try asking the MEGIN customer support directly?
@ebock
If you get further information about this topic, please post it here as it might help other users.
I have received a reply from MEGIN. The SSPs provided to MEG are also suitable for data analysis. As long as the ambient noise on the day of the measurement is similar to the ambient noise on the day the SSPs are created. In case of strong deviations (e.g. strong work on a nearby construction site) it could be helpful to determine daily SSPs for this purpose. In general MEGIN recommends to use tSSS. However, they could not comment that tSSS might have removed brain signal (as mentioned in the original post) without a detailed analysis of the dataset.