[FieldTrip] Motor beta activity - DICS solution more noisy than sensor data?
Haiteng Jiang
haiteng.jiang at gmail.com
Thu Nov 21 22:49:50 CET 2013
On 21 November 2013 21:46, <fieldtrip-request at science.ru.nl> wrote:
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> Today's Topics:
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> 1. Re: Motor beta activity - DICS solution more noisy than
> sensor data? (Eelke Spaak)
> 2. Re: Motor beta activity - DICS solution more noisy than
> sensor data? (Cristiano Micheli)
> 3. Re: Motor beta activity - DICS solution more noisy than
> sensor data? (Stan van Pelt)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 21 Nov 2013 18:27:43 +0100
> From: Eelke Spaak <eelke.spaak at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Motor beta activity - DICS solution more
> noisy than sensor data?
> Message-ID:
> <CABPNLUr577Rq=
> zBvahNkAp9rO9LTRimRWR09GbeC3vfEv1sXHg at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks for the input Vit?ria. Are you using Fourier input to
> sourceanalysis, or 'powandcsd'? I'm wondering whether the csd computation
> inside sourceanalysis might be to blame. Will investigate this tomorrow :)
>
> Eelke
> On Nov 21, 2013 6:01 PM, "Vitoria Piai" <v.piai.research at gmail.com> wrote:
>
> > Hi all, Eelke,
> >
> > Maybe adding to Eelke's remark, although I'm not working with motor beta
> > activity and lateralised index.
> > I'm also using DICS and my very clear, focal sensor-level effects all of
> a
> > sudden become localised to the whole brain or a whole hemisphere!
> > I happen to have heard from Jan-Mathijs that there may something going on
> > at the moment, but at least for now, Eelke, I don't think this error is
> > unique to our data (and I was actually going to post my incompatible
> > sensor-source results here soon, so now it's less work for me :)
> >
> > Looking forward to hearing your updates,
> > (I'm interrupting my source-level analyses for the time to get a better
> > feeling for the sensor-level data first)
> > Vit?ria
> >
> > On 21-11-2013 17:36, Eelke Spaak 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
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >
> >
> > --
> > Vit?ria Piai
> > PhD Candidate
> > Donders Institute for Brain, Cognition and Behaviour
> > Centre for Cognition, Radboud University Nijmegen
> > Montessorilaan 3, B.01.05
> > 6525 HR Nijmegen
> > The Netherlands
> >
> > Email : V.piai at donders.ru.nl
> > Phone : +31 24 3612635
> > www.vitoriapiai.com
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
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> ------------------------------
>
> Message: 2
> Date: Thu, 21 Nov 2013 13:39:30 -0500
> From: Cristiano Micheli <michelic72 at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Motor beta activity - DICS solution more
> noisy than sensor data?
> Message-ID:
> <
> CADW7XCCf9aAPYFTF9iCuMnRgYHA6hhoPBbex0ihkJNB_b3ah5Q at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear Eelke, very interesting topic. Please find my two cents below:
>
>
> On Thu, Nov 21, 2013 at 11:36 AM, 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.)
> >
>
>
> There might be issues with:
> - head positions/distance of single subjects in the dewar
> - something happening in the transition axial -> planar gradiometers
> conversion
> - orientation of the brain motor sources
> - inverse problem reconstruction
> - magnitude of the power effects for the different subjects
> - forward model issues
>
> Let me comment briefly on point 4. If the sources in the motor cortex are
> bilateral (as expected to different extents from ipsi to contra) and are
> temporally correlated, this constitutes an issue for the beamformer
> algorithm (van Veen et al.1993) especially if the sources are near (and
> lead fields highly correlated).
> There are workarounds to localize the single contributions of
> primary/secondary motor sources, but this implies the use of regional
> suppression (a nulling beamformer) and it is a tedious procedure to apply.
> Might be worth to look into that though. Let me know if you have interest
> in this.
>
>
>
> > 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).
> >
>
> On this point: using regularization is useful to invert the real(csd)
> matrix if it is ill-conditioned, but might blur the source reconstruction.
> On the other hand not using it might also be detrimental on the source
> reconstruction. Therefore applying it depends on the condition number of
> your csd. Is the matrix full rank? If not you might consider regularizing.
> Did you previously use ICA/PCA to get rid of artifacts? If yes that will
> have a negative effect on the condition number. and you might consider
> cranking down the ICA components rejection to the big spiky components -if
> any- and let the beamformer filter reject the smaller ones (in magnitude).
> Are you using cluster statistics based on the maxval? Maybe another
> statistics might give different results, given that the maxval might be due
> to artifacts (muscular, heart, ...)
>
>
> > 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.
> >
>
> Do all subjects sit with the top of the head at the same distance from the
> dewar? This is easily visualized by plotting the headmodel together with
> the head coordinates' sensors.
> By experience with CTF systems not all subjects' heads are at the same
> distance from the top (because they slip down, or they reposition 'cause
> they can't see out of the dewar, they also move!). This might hinder the
> SNR of the raw data to start with.
> It seems the grand average is still significant, but might be due to the
> contribution of a few good subjects.
> You may also want to consider the movement correction GLM method at the
> source level. Maybe it gives you back some SNR.
>
>
> > 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.
> >
>
> Yes, but it can also depend on different extents from FFT-level analysis.
> Have you played around with spectral smoothing, by for example lowering the
> number of tapers, or changing to a single condition contrast like
> activation vs baseline in the beamformer?
> What is the grand average vs single subject lateralization effect/single
> condition effect/ planar or axial effect? Is it there for all single
> subjects?
>
> I hope the comments helped a bit.
>
> All the best!
> Cristiano
>
>
> >
> > Thanks!
> > Best,
> > Eelke
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
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> ------------------------------
>
> Message: 3
> Date: Thu, 21 Nov 2013 21:45:49 +0100 (CET)
> From: Stan van Pelt <stan.vanpelt at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Motor beta activity - DICS solution more
> noisy than sensor data?
> Message-ID:
> <513733919.261511.1385066749005.JavaMail.root at indus.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Eelke, Have you tried comparing the results with a time-domain
> beamformer? You could e.g. try LCMV on 15-25Hz-bandpassed data. This should
> give you in theory similar results. Best, Stan ----- Oorspronkelijk bericht
> -----
> > Van: "Eelke Spaak" <eelke.spaak at donders.ru.nl>
> > Aan: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> > Verzonden: Donderdag 21 november 2013 18:27:43
> > Onderwerp: Re: [FieldTrip] Motor beta activity - DICS solution more
> > noisy than sensor data?
> > Thanks for the input Vit?ria. Are you using Fourier input to
> > sourceanalysis, or 'powandcsd'? I'm wondering whether the csd
> > computation inside sourceanalysis might be to blame. Will investigate
> > this tomorrow :)
> > Eelke
> > On Nov 21, 2013 6:01 PM, "Vitoria Piai" < v.piai.research at gmail.com >
> > wrote:
> > > Hi all, Eelke,
> > > Maybe adding to Eelke's remark, although I'm not working with motor
> > > beta activity and lateralised index.
> > > I'm also using DICS and my very clear, focal sensor-level effects
> > > all
> > > of a sudden become localised to the whole brain or a whole
> > > hemisphere!
> > > I happen to have heard from Jan-Mathijs that there may something
> > > going
> > > on at the moment, but at least for now, Eelke, I don't think this
> > > error is unique to our data (and I was actually going to post my
> > > incompatible sensor-source results here soon, so now it's less work
> > > for me :)
> > > Looking forward to hearing your updates,
> > > (I'm interrupting my source-level analyses for the time to get a
> > > better feeling for the sensor-level data first)
> > > Vit?ria
> > > On 21-11-2013 17:36, Eelke Spaak 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
> > > > ______________________________ _________________
> > > > fieldtrip mailing list
> > > > fieldtrip at donders.ru.nl
> > > > http://mailman.science.ru.nl/ mailman/listinfo/fieldtrip
> > > --
> > > Vit?ria Piai
> > > PhD Candidate
> > > Donders Institute for Brain, Cognition and Behaviour
> > > Centre for Cognition, Radboud University Nijmegen
> > > Montessorilaan 3, B.01.05
> > > 6525 HR Nijmegen
> > > The Netherlands
> > > Email : V.piai at donders.ru.nl
> > > Phone : +31 24 3612635
> > > www.vitoriapiai.com
> > > ______________________________ _________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/ mailman/listinfo/fieldtrip
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> -- Stan van Pelt, PhD Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognition Montessorilaan 3, B.01.19 6525 HR Nijmegen tel:
> 024-3616288
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> *****************************************
>
--
Haiteng Jiang
PhD candidate
Neuronal Oscillations Group
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Visiting address
Room 2.32
Donders Centre for Cognitive Neuroimaging
Kapittelweg 29
6525 EN Nijmegen
the Netherlands
Tel.: +31 (0)243668291
Web: https://sites.google.com/site/haitengjiang/
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