[FieldTrip] Problems with TMS-EEG dataset

[Stefan van Haren]

Dear community,

My name is Stefan and I am finishing my master thesis at the University
Medical Centre Groningen on a study with EEG-TMS data during language
tests. Here the subject names a picture on a screen while we administer a
train of 5 TMS pulses with a frequency of 5Hz. The TMS pulses are
administered at t=0ms and the picture is also shown at t=0ms. This means
that the final TMS pulse is administered at t=800ms. The biggest challenge
remaining is the fact that I want to analyse the ERP (mainly the P300
component) which is located between the second (200ms) and third (400 ms)
TMS pulse. This means that the data in between the TMS artefact must have a
sufficient quality. I have compiled a processing pipeline to process the
data;


   1. Divide into trails.
   2. Remove TMS artefact (by removal and interpolation)
   3. Filter the data (40 Hz low pass, 1Hz high pass)
   4. Remove any bad channels and trials.
   5. ICA

I can provide the script that I use but it is quite large and might not be
needed for my question. When following this pipeline, the data is processed
quite nicely, but still some ‘problems’ remain, See the plot below where
the first image is the averaged raw data and the second image is the
averaged filtered data.
[image: image.png][image: image.png]


As you can see, there are still problems with a lot of the channels, for
example, the most negative orange channel, which is visible in both plots.
This plot seems to tend to rise but seems to be ‘reset’ after each TMS
pulse (at 0.20, 0.40, 0.60, 0.80 sec). This decrease is caused by the
interpolation of the TMS artefact. Does anyone have any idea what this
might be, and how I can solve/prevent this problem? It is present in a lot
of channels and at this point, I cannot reliably calculate an ERP. I also
noticed that this effect is mostly present in the channels that are close
to the TMS stimulation sites. Any help would be appreciated greatly.

Best,

Stefan
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