[Mne_analysis] Noise covariance matrix

Thu Mar 26 20:19:26 EDT 2020

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Thank you very much for your help!

On Thu, Mar 26, 2020 at 11:28 PM Denis A. Engemann <
denis-alexander.engemann at inria.fr> wrote:

>         External Email - Use Caution
>
> Hi Laura,
>
> I’m not sure “totally wrong” is the right category.
> I would rather  ask why you need to filter your evokeds at the evoked
> stage and
> why you want to avoid filtering at the raw level.
> Do you have scientific reasons to do this, related to the phenomenon of
> investigation?
> If not, I would stick with a more standard pipeline.
> It is likely that your problem will dissolve when just filtering at the
> the raw-stage.
> If not, there may be something to understand about your data.
> Btw., note that by performing Maxfilter, depending on whether you have
> used tSSS, you may have already substantially filtered your data in terms
> of frequency content.
> So using the unfiltered covariance is not entirely implausible.
> But perhaps you can do better.
>
> Hope that helps,
> Denis
>
> > On Mar 26, 2020, at 8:21 PM, Laura Munkki <lauramunkki at gmail.com> wrote:
> >
> >         External Email - Use Caution
> >
> >
> > Hi Denis,
> > Thank you very much for your answer,
> > The last question: is it acceptable to use the NCM from unfiltered
> epochs (after the maxfiltering and ICA) for modelling ERPs which were
> filtered after averaging, or it would be totally wrong?
> > Best,
> > Laura
> >
> >
> > On Thu, Mar 26, 2020 at 7:10 PM Denis A. Engemann <
> denis-alexander.engemann at inria.fr> wrote:
> >         External Email - Use Caution
> >
> > Hi Laura,
> >
> > Regarding 1) I would see no a priori reason for filtering once more,
> also filtering is more accurate on the long raw time series. Filtering at
> later  stages may be helpful for exploring ideas but if you can avoid
> that’s better.
> > Regarding 2) It depends if you at least apply maxfiler & ICA to the
> data. If you don’t temporally filter, your noise-covariance will be more
> strongly influence by low frequencies, e.g., environmental noise, if you
> filter, it may help suppressing spatial patterns due to background brain
> activity e.g. alpha band, hence, yield enhance SNR for your activity of
> interest.
> > If you don’t filter, it will give a solution that looks more like one
> that is based on the noise covariance from empty room. But applying the
> same preprocessing in terms of SSP/SSS/ICA is important in any case.
> > If it helps, think that the noise covariance defines a noise model for
> MNE/dSPM.
> > The inverse solution will be relative to that model.
> > If you have a doubt about the content of your covariance, see the
> plotting trick in this tutorial
> https://mne.tools/dev/auto_examples/inverse/plot_mne_cov_power.html?highlight=apply%20inverse%20cov
> to visualize the diagonal of the  covariance as topomap. It can  give you a
> feeling for whether you capture brain sources in your covariance.
> >
> > Hope that helps,
> > Denis
> >
> > > On Mar 26, 2020, at 4:43 PM, Laura Munkki <lauramunkki at gmail.com>
> wrote:
> > >
> > >         External Email - Use Caution
> > >
> > >
> > > Hi Denis,
> > > 1. If the raw data is filtered before the ICA, should one filter
> averaged responses again before source modelling?
> > > 2. In case of the situation I described above, is it possible to use
> NCM calculated for unfiltered NCM-epochs, or it is totally wrong?
> > > Thank you again!
> > >
> > >
> > > On Thu, Mar 26, 2020 at 5:19 PM Denis A. Engemann <
> denis-alexander.engemann at inria.fr> wrote:
> > >         External Email - Use Caution
> > >
> > > Hi Laura,
> > >
> > > To me the safest thing is bandpass filtering at raw stage, e.g., prior
> to ICA.
> > > Then you keep processing identical for data and noise covariance and
> just use the baseline segments from the otherwise  identically processed
> epochs.
> > > Have you tried that?
> > >
> > > Denis
> > >
> > > > On Mar 26, 2020, at 4:11 PM, Laura Munkki <lauramunkki at gmail.com>
> wrote:
> > > >
> > > >         External Email - Use Caution
> > > >
> > > >
> > > > Hi Denis,
> > > > Thank you very much for your reply.
> > > > I did maxfiltering and ICA for the raw data, so these steps are
> applied for both types of epochs, evoked responses and NCM. But I did not
> use any band-pass filters before averaging. I filtered only averaged ERPs
> just before source reconstruction. So, if I filter NCM epochs, it will not
> be the same. My question is: when should I apply a band-pass filter for the
> NCM? I tried to apply it to the NCM-epochs file, but the result was
> distorted: instead of sources around auditory cortex I've got several
> sources in unpredictable locations. But when I tried to use NCM calculated
> for unfiltered NCM-epochs, the sources were around auditory cortex and had
> much stronger amplitude.
> > > > Looking forward for your answer,
> > > > Thank you very much for helping me,
> > > > Laura.
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