[Mne_analysis] identifying insensitive sensor time series for rejection

[Talitha Ford]

Hi all,

I am using MNE to analyse some MEG mismatch negativity (MMNm) data. I have ~170 trials of a ‘standard’ and ~170 trials of a ‘deviant’, the MMN comes from the average of the deviant minus the average of the standard for each participant.

I have some data that looks insensitive to the deviant response, but would like an objective way of identifying and removing the data from my analyses. I’m sure its out there, but is there a function/s to test whether a section of the averaged deviant time series from one channel (MEG1621 from 10oms to 200ms) is significantly greater than zero? The data is baseline corrected, so I presume against zero would be the correct comparison.

Also, I just wanted to let you know that subtracting one average() from another results in the average of the two rather than one minus the other. For example: dev_ave - stand_ave = (dev_ave - stand_ave)/2. I’m not sure if this is intentional, or an error in the code for average()?


Sorry if this info is out there already!

Cheers,
Talitha