[FieldTrip] Motor beta activity - DICS solution more noisy than sensor data?

[Charidimos Tzagarakis]

Hi Eelke,
Provided there is no major recent revision of the DICS code, I would have
expected motor desynchronisation to show up pretty well. Are the maps shown
at source and channel level straight differences of L and Right hand
conditions at the beta band (I hope I am correctly interpreting your
paradigm) ? If so it might be helpful in pinpointing the problem/as a
sanity check  to see what happens when you use beta desynchonisation (ie
change relative to the baseline) instead for each condition, and see
source/channel maps of that separately for L and R and then when you take
the difference. I suppose the main element this checks for is whether L and
R conditions have the same baseline.
This doesn't immediately explain why source and channel results are
different but in the absence of any other clues it may be a way to 2ble
check the whole process.


Another point to consider is that, although beta changes should appear in
all subjects, it is possibly true that there are individual differences in
the actual beta range and frequency bin of maximum effect. If you are using
the same settings for all subjects when you beamform with DICS you may be
missing some of the effect (true, this is also the case for channel data
but there may be subtle differences that add up - there are many voxels and
few channels). I believe it may be useful to see what happens when you run
the beamformer tailored to each subject's particular beta characteristics
(ie change the "foi" for each subject, keep the tapsmofrq the same -
possibly smaller) and then combine everything (you'll need of course to
come up with a relative metric such as perc. change when you combine all
subjects to account for the slightly different frequencies you used )

Best,
Haris

Charidimos [Haris] Tzagarakis MD, PhD, MRCPsych
University of Minnesota Dept of Neuroscience and Brain Sciences Center




On 21 November 2013 10:36, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:

> Fellow FieldTrippers,
>
> Currently I am looking at a contrast for left- versus right-hand index
> finger button presses. As expected, on sensor level (combined planar
> gradient, grand average) I see a clear lateralisation in beta band
> power starting at least 0.5s before the button press (see
> https://db.tt/Rtch3Qjy). Both 'blobs' are significant; there is
> clearly more beta power ipsilateral to the response hand. I would
> prefer to do further analyses on source level, so I attempt to
> reconstruct the sources for this effect using DICS beamformer (common
> filter, applied to both conditions separately; fixedori and realfilter
> = 'yes'). The grand average results for this (again contrast left vs
> right response hand) are shown at https://db.tt/IBQZG0d8 . (Ignore the
> R/L-flip, this is radiological convention.)
>
> As you can see, the source level solution is much more blurry than on
> sensor level. This picture is without using any regularisation (lambda
> parameter), the results are even worse when I use lambda = '5%'. The
> negative blob (right hand higher power than left) becomes 'marginally
> significant' on source level (p ~ 0.06) where it was p < 0.001 on
> sensor level. The positive blob is nowhere near significant. Also, the
> individual results are much less topographically consistent on source
> than on sensor level (explaining the worse statistics).
>
> I have checked the segmentation of my MRIs, the 'gray' seems to be
> nicely within the head all the time. Also, I have manually verified
> the alignment of headmodel, sourcemodel, and gradiometer information
> for all subjects.
>
> As a final note, the above sensor-level plot was taken from a 'slice'
> out of a planar-gradient time-frequency analysis (mtmconvol). The
> ingredient for the beamformer was an mtmfft fourier spectrum on the
> axial gradiometer data, obtained for just the time-frequency range of
> interest (subselect toilim [-0.5 0], mtmfft foi = 23, tapsmofrq = 7).
> When I compute condition-averaged power based on these fourier spectra
> and look at the contrast, the results are again as expected:
> https://db.tt/n2P3UKcQ (of course less localised because of axial
> gradient vs planar). The freq structures underlying this contrast are
> exactly the same as those going into ft_sourceanalysis, so the problem
> must be in the source analysis step (and/or in the preparation of the
> geometric information, although these seem fine by visual inspection).
>
> Does anyone have any idea that might explain these seemingly
> contradictory results? I would have expected demixing to improve
> signal-to-noise ratio, rather than worsen it.
>
> Thanks!
> Best,
> Eelke
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