[Eeglablist] How to do data decomposition with ICA?

[Scott Makeig]

Hannu  -  The  'CI' ( = ??) artifact has the same scalp projection in all
conditions, then ICA will separate it into a single component (assuming its
activity is not linearly related to other, spatially-varying phenomena).
To most cleanly separate the artifact from the rest of the data, it is best
to decompose all the data at once. Of course, if the other sources in the
different experimental blocks are quite different (say, as an extreme
example, if the subject in the three blocks was respectively awake, asleep,
and having an epileptic seizure), then separate decompositions followed by
artifact component comparison and matching might be more effective.

Note that ICA (instantaneous ICA, including infomax, runica, binica, Amica)
does not pay attention to the time waveforms at all, just the collection of
scalp maps for all the time points (in no particular order).

Scott Makeig

On Wed, Jul 28, 2010 at 12:09 AM, Hannu Loimo <hannu.loimo at helsinki.fi>wrote:

>
> Hi,
>
> We are using ICA to remove CI-artefact from our data. ICA seems to find
> pretty easily at least some of the artefact induced by CI-devise. There are
> 8 events in our experiment and two of those events (duration and gap
> deviants) produce different form of CI-artefact in time domain. All events
> are made out of syllable sequence ta-ta-ta. Gap deviant means that second
> syllable starts 100ms later than in other events. Duration deviant means
> that the whole ta-ta-ta sequence lasts 50ms longer. Presumably CI-artefacts
> rising from different events have same kind of spatial distribution and
> presumably most significant difference is how these artefact peaks are
> located in time. So basically there are three differend shapes of
> CI-artefact present in time domain: one for gap deviant, one for duration
> deviant and one for other six stimuli. After doing ICA for whole dataset
> (all events) CI-artefacts emerging from different events seem to be
> contained in one component and not many. My question is:
>
> Is it a problem to do ICA for whole dataset or shoud ICA be done for
> individual events separatelly? Size of dataset is 2000 epochs and separating
> events into different dataset would end up datasets as small as 150-200
> epochs (too few for ICA?). So far we have been doing ICA for whole datasets,
> then removed CI-artefact components and after that separated data into
> different events. What I'm asking is does it affect the final outcome of our
> separate event ERP composition if you remove CI-artefact components that are
> calculated according to all events or is it same if you do ICA for single
> events and then remove components?
>
> thanks,
>
> Hannu
>
>
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-- 
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0961, http://sccn.ucsd.edu/~scott
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