[Mne_analysis] SSP projection and the forward gain matrix

[Ying Yang]

Thanks, Alex.  It is very helpful!

Best,
Ying


On Tue, Jul 1, 2014 at 10:42 AM, Alexandre Gramfort <
alexandre.gramfort at telecom-paristech.fr> wrote:

> hi Ying,
>
> > The noise is decomposed to
> > bn(t) = U * cn(t) + e(t),
> >  where e(t) is white noise.
> > Let y(t) be the sensor signal and x(t) be the source signal
> >
> > y(t) = G x(t) + bn(t)
> > so if we apply the SSP operator  (I - UU'),
> >
> > (I-UU') y(t) = (I-UU')G x(t) + (I-UU') bn(t)
> >                    = (I-UU')G x(t) + (I-UU') e(t)
>
> this is correct.
>
> > So I thought when applying the SSP to the sensor data, the forward matrix
> > should also be multiplied by the operator.
>
> yes
>
> > But when I tried to read through  the python code in
> > "mne.minimum_norm.inverse", I did not find this kind of operation.
> > Am I missing something or is it the case that  the operator should not be
> > applied to G?
>
> it is applied to G but via the whitening matrix to which has been applied
> the SSPs.
>
> hope this helps,
>
> Alex
>
> > If the latter is true, why is it true?
> >
> > Thanks so much.
> >
> > Best,
> > Ying
> >
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