[FieldTrip] Why are time-frequency results so much different from Beamformer source localization?

[Stephen Whitmarsh]

Hi Patrick, (and Tzvetan - who responded in the meantime),

I agree that you should start with a good correspondence between your
initial results (wavelets), and the power difference you are trying to
localize (with mtmfft).

Wavelets and fft methods can result in very similar - practically identical
- results, but that depends on a number of parameters, especially
concerning frequency-smoothing; Wavelets are typically defined in terms of
nr. of cycles, while fft methods are defined in terms of time-windows.
Wavelets defined in nr. of cycles will have a decreasing time-windows with
increasing frequency, while with mtmfft time windows will remain the same.
Because of this, frequency smoothing will increase with frequency with
wavelets, and stay the same with a constant time window. Of course, you can
make the fft time window frequency-dependent, as is described in the
frequency-analyses tutorial, to make them more comparable. Secondly, the
fft method allows you to specify frequency smoothing when you use Sleppian
multitapers (cfg.taper = 'dpss'). To be clear, you should be able to
recognize these differences in frequency smoothing/resolution when looking
at the different TFR plots. Currently they look too different, probably
because of something else (baseline?) than a wavelet-fft difference.

I would advise making a 'full' TFR with mtmfft similar as your wavelet
results so that you can properly compare them. This allows you to also set
the best parameters for smoothing/timeperiods. In fact, you can use the
multitaper approach to more accurately extract the power in a certain
frequency band. Only then compare the topo's, and only then do the
beamformer, so you will pick up any unexpected results.

Because of different contrasts/baseline correction, I cannot compare the
topo's / beamformer results.

Bon courage,
Stephen









Op vr 13 nov. 2020 om 11:30 schreef Patrick Wiegel <
patrick.wiegel at sport.uni-freiburg.de>:

> Dear Field-trip community,
>
> I am working on EEG data from a motor learning task. in the first part of
> my analysis, I performed a time-frequency analysis (Morlet wavelet method)
> and cluster-based permutation test. I compared two different conditions
> (correct & incorrect movements) within subjects and found a significant
> difference in the beta band (20-35 Hz) when subjects were provided with
> feedback. I attached the topographical plot from one subject that
> illustrates the difference between the conditions at the selected time
> point and frequency (dif_morlet). As you can see, beta power was higher in
> one condition in lateral frontal electrodes.
>
> Now, I would like to better spatially locate the effect for this single
> subject. For this purpose, I followed the Beamformer tutorial on the
> website. In the first step, I selected the raw data of interest (at the
> time where the effect was seen) and performed frequency analyses for the
> 20-35 Hz range (mtmfft, contrast between conditions shown in dif_mtmfft).
> There is an apparent difference between dif_morlet and dif_mtmfft and I am
> wondering why this is the case? One apparent reason is that the
> time-frequency data were baseline corrected and the frequency data from
> mtmfft not.
>
> Using the power and CSD data from mtmfft, I performed the source analysis
> with a standard MRI and head model. The source was located in the left
> hemisphere (source plot), which is in stark contrast to the time-frequency
> data (dif_morlet). I am aware that the source analysis is based on a lot of
> assumptions (conductivity etc.) that influence the calculations but it is
> very difficult to make sense of such discrepancy.
> Maybe it is necessary to also baseline correct the mtmfft data before
> inputting them to the source analysis? Or doing the contrasting source
> localization betwee a single condition and the corresponding baseline data
> before contrasting the 2 conditions?
>
> I am providing all necessary files and scripts (TF_analysis & BEAMFORMER)
> if anyone is interested to reproduce the results that I am showing and
> reporting for this single subject (
> https://github.com/PatrickWiegel/EEG-Beamformer-Source-localisation).
>
> I would appreciate any help and discussion on that.
>
> All the best,
> Patrick
>
>
>
>
>
> *Patrick Wiegel*
> Department of Sport and Sport Science
>
> University of Freiburg
> Sandfangweg 4
> 79117 Freiburg i. Br .
>
> phone: +49 (0)761/ 203-4550
> email: patrick.wiegel at sport.uni-freiburg.de
> <patrick.wiegel at sport.uni-freiburg.de>
> web: www.sport.uni-freiburg.de
>
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> https://doi.org/10.1371/journal.pcbi.1002202
>
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