[Eeglablist] ICA suggests weirdly low rank

[Cedric Cannard]

Yes my first guess would be bridged electrodes if you used gel.


Cedric



On Tuesday, June 11th, 2024 at 11:02 AM, Makoto Miyakoshi via eeglablist <eeglablist at sccn.ucsd.edu> wrote:

> Hi Ivonne,
>
> 1. What number do you get if you run dataRank = sum(eig(cov(double(EEG.
> data'))) > 1E-7); Use that number for the 'pca' option.
>
> 2. A few things I can think of if you say your data rank is lower than
> predicted.
> 1. The first thing is the unit of your EEG data. If you are using mV
> or even V instead of microV, then you'll lose resolution by 3
> and 6 orders
> of magnitude. The ICA's empirical 'resolution' of IE-7, suggested by Sven
> Hoffmann, is in an absolute sense. If you use nanoV, you'll have the same
> tolerance at 1E-10, I predict.
> 2. Electrodes were bridged by conductive gel. I haven't experienced
> it myself, but just 15 min ago one of my colleagues told me that massive
> bridging happened in one of the projects. Particularly, if you use a
> cloth-based electrode cap, electrodes at around Cz tend to be pushed up.
> You may tend to compensate it by injecting a lot of gel into the
> electrodes
> of that region (indeed, you may have ground and initial
> reference electrodes in that area).
> 3. Your data may be heavily band-pass filtered. Narrow band signals
> have less degrees of freedom to be independent. I think Claude Shannon
> mentioned narrow-band signals can carry less information.
>
> Off the top of my head, I can think of the above three things. If I were
> you I would check those three things to start troubleshooting.
>
> > Also, I am unsure whether I should "force" it to compute 25 ICs using the
>
> gui or the 'pca' option, could this be detremental to ICA results?
>
> If dataRank defined as dataRank = sum(eig(cov(double(EEG.data'))) > 1E-7);
>
> is <25... you may see Kim's ghost in your result! Always use numICs <=
> dataRank.
>
> Makoto
>
>
> On Tue, Jun 11, 2024 at 11:51 AM Ivonne Weyers via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
> > Dear list members,
> >
> > I am experiencing some issues running pop_runica, namely that it
> > produces weirdly low rank.
> >
> > I have a 27-channel infant dataset recorded with a single channel
> > reference (Fz), for which I perform the following steps before running
> > ICA: filter, remove bad channels, interpolate, re-reference to average
> > reference and adding Fz back to the data, epochize (this does not reduce
> > the amount of data by much, just truncates the continuous data), reject
> > only extremely large artifacts.
> >
> > I understand from previous discussions as well as the papers on this
> > issue that my data becomes rank deficient by n if I interpolate n
> > channels. (Is rank reduced further by -1 due to average re-ferencing
> > even if the original reference is added back to the data?) When I run
> > pop_runica on a 27 channel data set in which channels have been
> > interpolated, however, eeglab returns a substantially lower rank, e.g.
> > 22 when two channels have been interpolated (which should be 25; or 24
> > if average referencing reduces futher).
> >
> > From what I have read in the mailing list, most people experience the
> > opposite, i.e. rank() failing to identify rank deficiency, but I haven't
> > found anything on weirdly low rank. Does anyone have an idea what may be
> > causing this?
> >
> > Also, I am unsure whether I should "force" it to compute 25 ICs using
> > the gui or the 'pca' option, could this be detremental to ICA results?
> >
> > I would appreciate any ideas on this, also let me know if I failed to
> > include any details on the data.
> >
> > Thank you & best,
> >
> > Ivonne
> >
> > --
> >
> > Dr. rer. nat. Ivonne Weyers (she/her)
> > Psycholinguistics Group
> > Institute of Linguistics
> > University of Vienna
> > Sensengasse 3A, Room 06.12
> > 1090 Wien
> >
> > ivonne.weyers at univie.ac.at
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