Source reconstruction of power spectral density values

Support & Discussions
1

Hello forum!
I would like to obtain the source image for a topography of power values at one selected frequency extracted from a PSD.
The background is that we have a very specific pipeline to extract oscillatory peaks in low frequency bands, which requires first removing the 1/f slope (we use the IRASA technique), and then selecting a narrow peak frequency.

My bold attempt was to take the topography of power values (102) magnetometers, put them into a EvokedArray and source-project with dSPM. I run into scaling problems and overflow errors, which I assume come from the fact that my noise-covariance computed from an empty room recording has a scale of femtotesla, but the power values range roughly between -2 and 2.

I am aware that there are other alternatives, like source-projecting the data covariance, or computing the PSD in source space, but my goal is to visualize this particular power topography.

My questions:

  • Is my bold approach wrong for reasons other than the scaling?
  • If the approach can be defended, how can I overcome the scaling problem? I tried to just rescale the power values before applying the inverse. I do get results, but this feels very hacky.

Very grateful for any insights!
Sophie

2

you cannot do this. You need polarity information to have dipole locations. With the complex valued spectrum it could work but not with only power magnitude.

Alex

3

Thanks Alex, you confirmed my doubts.

4

I want to keep the 1/f removal, which is achieved by resampling the time-domain data at non-integer numbers, computing the PSD and averaging to remove narrow peaks (IRASA).
Performing this in source space will be computationally heavy.
Any suggestion on how to proceed?

5

I don’t know this method in details but reading what you say maybe source localize using DICS or dSPM in spectral domain after the
“resampling time-domain data at non-integer numbers”?

Alex