[Eeglablist] ICA decomposition of possibly 2 different conditions....

Julie Onton julie at sccn.ucsd.edu
Mon Jan 18 12:42:18 PST 2010

With regard to the comment about decomposing dissimilar data separately,
perhaps a distinction should be made. Arno is correct that by far the easiest
approach is to look at *activity* differences within single sources. However,
what I point out in the paper is that vastly different behavioral conditions
(ie, sleep and wake) may show fundamentally different active sources. Within
most experimental paradigms, the difference between conditions is MUCH less
than the difference between sleep and wake, therefore warranting a single
decomposition for both conditions. For your own curiosity, try decomposing the
2 conditions separately and see how similar your components are (assuming you
have enough data to get clean decompositions).

Now, the amount of *good* data that you will need is, of course, a slightly
hazy subject. I have previously recommended a points per weight factor of 25
or more, but this is based on 71 channels (dimensions) and 256 sampling rate.
More channels require more data, of course, but I'm not sure if the points per
weight factor remains the same when the channel number scales up. The more the
better usually... I got good decompositions for ~215 channel EEG with about an
hour's worth of data. A half hour would likely not have been enough. For 128
channels, you can get away with less data... perhaps a half hour even, but not
less, I would guess. Sorry for the highly anecdotal answer, but I have found
that there is a lot of variability between subjects even with comparable
amounts of data... therefore pointing to individual differences in the
'quality' of data that ICA is good at decomposing. But that's just a theory.

Good luck, Julie

Julie Onton, PhD

> Dear all,
> as
> it follows from J Onton’s paper: “…… jointly decomposing data from awake
> and
> sleeping conditions might not be optimal if the EEG source locations in these
> portions of the data differed……” we do need to separate 2 conditions and than
> perform ICA on
> each of them separately.
> I
> guess it should not be a problem cutting out some of the data (artifacts) from
> EEG recording using EEGLAB function Reject an then running ICA on this data,
> but then the question of
> enough data arises. It was suggested in several publications to use k*n2 data
> points (where k is a coefficient and n is a number of channels), to get a
> stable results of the ICA.  It was suggested to use k of 20 by some (128
> channel EEG) (McMenamin 2009) or even bigger. What experiences do you have?
> How
> much data will one need to get stable ICA components in 128 channel recording?
> And
> thanks a lot for the previous answers, you help a lot.
>       _______________________________________________
> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> To unsubscribe, send an empty email to eeglablist-unsubscribe at sccn.ucsd.edu
> For digest mode, send an email with the subject "set digest mime" to
> eeglablist-request at sccn.ucsd.edu

More information about the eeglablist mailing list