Hi,
I have become a huge fan of Brainstorm/Nirstorm in my analyses of fNIRS data, and I have learned the use of the software through the excellent workshops from 2018-2024.
But, does Brainstorm/Nirstorm have options for performing subtraction of extracerebral noise based on the use of short channel fNIRS data?
Thank you very much for your help.
Hello,
Thanks a lot for your feedback on Nirstorm 
You can use the process called NIRS > pre-process > Remove superficial noise
it is using the average of the short-sepration channel to subtract the extracerebral noise from the nirs signals.
You can find the short channel using either their name (ie. S1D17, S2D17...) or using a source-detector distance threshold (ie < 1 cm).
The baseline is used to find how to perform the subtraction; the subtraction is then applied on the entire signal. You can use the entire signal if your recording is relatively short and has no major motion artifacts. Otherwise, we recommend using a clean portion of your data signal.
Let me know if you have any questions,
Edouard
Hello again Edouard Delaire,
Thank you for the reply and answering this question, and when I read your answer, I am a bit ashamed that I did not figure this out myself😊. It is clearly stated in the 2022 workshop, I was just used to describing it through different terms.
But I was - in the end - able to publish the article (https://www.mdpi.com/1424-8220/25/6/1807), and I have now adjusted my protocols to also take removal of the superficial noise into account. I will use this in my next publication.
Thank you again.
Best regards,
Steffen
