Question about ICA template matching with different number of channels

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Dear List,

I’m looking into removing ICA components in real time, and found that one way to do so is to store a numpy array of template IC derived from existing data, and use the corrmap() function to find components in the current ICs that best correlate with this template.

However, I noticed that the IC array has the length of number of good channels. Given that different acquisition runs often have different bad channels identified, I wonder what would be the best practice to overcome the channel mismatch between the stored template and running data. Should I:

  • Interpolate both the data used to generate IC templates and the running data so that both include all channels?
  • Interpolate both the template IC and ICs from the running data?
  • Interpolate template IC or the data, then remove entries that correspond to bad channels in the running data?
  • Something else?

There was a similar question from the archive but seems still open:

Thanks in advance,
Yaqing