[Eeglablist] How to do data decomposition with ICA?

Hannu Loimo hannu.loimo at helsinki.fi
Fri Jul 30 05:06:37 PDT 2010

Thanks for your anserw Scott

By CI I ment cochlear implant.


On Wed, Jul 28, 2010 at 8:02 PM, Scott Makeig <smakeig at gmail.com> wrote:

> 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<http://sccn.ucsd.edu/%7Escott>
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