[Eeglablist] Problems with rank computation - ICA

[Tarik S Bel-Bahar]

If using normal runica, you could pca reduce by one dimension, to reflect
the reduction by one rank, because of average referencing. Amica from jason
palmer should avoid these issues. Overall, your decomposition should look
okay and interpretable, even if you are getting those messages, especially
if you have followed all other preprocessing steps such as filtering,
removing baseline, and artifactual period removal. There was some
discussion about rank dimensions in data on previous eeglab discussions,
which you can search for, including a note about that warning message that
you are getting, but I dont think a final principled solution was setup.
On Feb 19, 2012 10:22 AM, "Marco Montalto" <montaltomarco at onvol.net> wrote:

> Dear all,
>
> I have data from 13 subjects which I am filtering, removing bad channels,
> re-referencing to average, epoching and then selecting epochs. When I run
> ICA I get the following warning (example from one particular dataset):
>
> Warning: fixing rank computation inconsistency (31 vs 30) most likely
> because running under Linux 64-bit Matlab
>
> And I get as many IC components as there are remaining channels.
>
> But for some datasets, which have been processed similarly to the other
> datasets, ICA correctly gives one component less than there are remaining
> channels.
>
> I have switched from single precision to double precision and now all
> datasets, after running ICA, give equal number of components as there are
> remaining channels (but still giving the warning message above).
>
> I am using EEGLAB version 10.2.5.8b running on MATLAB version 7.12.0.635
> (R2011a) on a Macbook Pro (Dual Core).
>
> Can anyone give me some advise regarding this warning? Should I ignore it
> and continue working with double precision or am I doing something wrong?
>
> Thanks!
>
> Marco
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