[FieldTrip] ICA in TMS-EEG

[Bingshuo Li]

Dear Max, Jim and Cristiano,

Thank you so much for sharing your experiences! I found your comments very
helpful. I will certain try the things you suggested and see how the ICA
works this time.

In addition, given that I have EOG and ECG recorded (but with different
references), maybe it will also be beneficial if I calculate the coherence
between the ICA components and EOG and ECG signals.

Furthermore, I think it will be very beneficial to the field if someone
with rich experiences in applying ICA in TMS-EEG can write a paper on
manual artifactual components recognition! ;)

Regards,

-----
Bingshuo Li (MSc. candidate), Neuroprosthetic Group, CIN, Uni Tübingen


On Wed, Nov 27, 2013 at 2:59 PM, Cristiano Micheli <michelic72 at gmail.com>wrote:

> Dear J.D., Max and Bingshuo,
>
> A brief comment: to be more confident about the correlative nature of an
> artifact being an artifact (a.k.a. unwanted interference) I always consider
> three things: topographies, time courses and spectra. The last one too,
> since it might inform about spectral components not evident at the bare eye
> from the time courses.
> I'm not familiar with artifacts in TMS, but in all cases experience helps,
> especially if you see the same pattern in many subjects, in other published
> studies, from colleagues' data or from independent evidence (e.g.
> concomitant electromiography recorded from the facial muscles, for muscular
> artifacts identification).
>
> HTH
> Cristiano
>
>
>
>
>
> On Wed, Nov 27, 2013 at 3:28 AM, Herring, J.D. (Jim) <
> j.herring at fcdonders.ru.nl> wrote:
>
>> Dear Bingshuo,
>>
>>
>>
>> I agree with Max that it would be beneficial to see the timecourses as
>> well. Also, in case of ICA on TMS-EEG data I find it usefull to timelock
>> average the time courses of the ICA components to the onset of the TMS
>> pulse. That helps in identifying components that are related to the TMS
>> pulse.
>>
>>
>>
>> Just from looking at the topographies I would say that component 7 is too
>> posterior for being a cranial muscle artifact given that you are
>> stimulating M1. Also, cranial muscle artifacts related to the TMS pulse
>> usually last up to about 15ms after stimulation onset (see for example:
>> http://fieldtrip.fcdonders.nl/_detail/development/tms/art_cranial_muscle.png?id=tutorial%3Atms-eeg) unless you are actually referring to a decay artifact (
>> http://fieldtrip.fcdonders.nl/_detail/development/tms/art_decay.png?id=tutorial%3Atms-eeg)
>> , which can last up to one second. You said that you cut and interpolated
>> up to 18ms after stimulation so you should not see any cranial muscle
>> artifacts related to TMS.
>>
>>
>>
>> Too me component 7 looks more like a topography related to posterior
>> alpha oscillations, however, to be sure we need to see the time courses.
>> Component 13 and 18 might be neck muscle artifacts, however, without
>> performing a timelock analysis of the ICA components and inspecting the
>> time courses it is hard to tell whether these are due to the TMS-pulse.
>>
>>
>>
>> Component 42 and 54 could indeed just reflect two bad channels, at least
>> they seem to contain some variance that cannot be explained by a
>> combination of the other channels.
>>
>>
>>
>> Best,
>>
>>
>>
>> Jim
>>
>>
>>
>> *From:* fieldtrip-bounces at science.ru.nl [mailto:
>> fieldtrip-bounces at science.ru.nl] *On Behalf Of *Bingshuo Li
>> *Sent:* dinsdag 26 november 2013 18:26
>> *To:* fieldtrip at science.ru.nl
>> *Subject:* [FieldTrip] ICA in TMS-EEG
>>
>>
>>
>> Dear FieldTrip Community,
>>
>> I recently started to analyze some TMS-EEG datasets and I encountered
>> some questions regarding to using ICA to remove eye movement/muscle
>> artifacts in our EEG data. As I am quite new to the analysis of TMS-EEG, I
>> would like to inquire the FT community for some hints or suggestions. Below
>> are the details of my questions:
>>
>> //Description of Data Processing//
>>
>> - EEG with 64 channel, sampling frequency 2500 Hz, electrode impedance
>> less than 5 kOhm
>>
>> - Every epoch consists of 1s prior to and 1s after TMS (130-150 trials
>> per subject)
>>
>> - TMS contaminated data points were cut out symmetrically -18ms to +18ms
>> relative to TMS onset. Cubic spline interpolation is used to fill in the
>> cut.
>>
>> - Bandpass 0.5 - 80 Hz, with BUT and filter order 3.
>> - Discrete Fourier transform filter (cfg.dftfilter) to remove 50 Hz line
>> noise
>>
>> - Visual inspection and rejection of trials with obvious unstable signal
>> or channels.
>>
>>  //ICA//
>>
>> - ICA algorithm: runica
>>
>> - Demeaned data for ICA training (baseline is defined as the entire epoch
>> -1 to +1s)
>>
>> - Unmixing matrix applied to non-demeaned data for component removal
>>
>> /////QUESTIONS/////
>>
>> Please see the image below for a typical result of ICA from a subject
>> with TMS applied at M1 (32 epochs for ICA training):
>> https://www.dropbox.com/s/chwo2jnwi72saba/ica1.png
>>
>> Q1: It seems obvious to me that component 1 and 2 are of eyeblink origin.
>> However, what about component 5, 12, 20, 28? Topology-wise, they seem to
>> have a very anterior origin, but data in the time domain does not seem to
>> correlate with component 1 and 2 very well (judging visually..)
>>
>> Q2: What can you say about components 7, 9, 13 and 18? Are these cranial
>> muscle artifacts?
>>
>> Q3: Also, for components 42 and 54, given their high focality, are these
>> more or less a indication of bad/unstable electrodes?
>>
>> - I guess maybe I am asking too many questions. I think my main problem
>> here is that I do not know what can be a good procedure / rules in manually
>> selecting ICA components for rejection? (I tried to look in the literature
>> but I couldn't find any that can answer my questions). And sometime I have
>> the feeling that my ICA results look like a mess and maybe there were
>> something wrong with my pre-processing or even data collection?
>>
>> Thank you guys in advance for any input! I look forward to hearing from
>> you!
>>
>> Regards,
>>
>> Bingshuo Li
>>
>> MSc. Student, Neuroprosthetic Group, CIN, Uni Tübingen
>>
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