[Eeglablist] ICA for artifact removal with few channels

[Becky Prince]

Thanks very much for the response, David!

____________________________________________

Becky Gilbert (nee Prince)
PhD Researcher

http://www.york.ac.uk/psychology/staff/postgrads/becky.gilbert/
Lab C120
Department of Psychology
University of York
Heslington, York, YO10 5DD, UK

On 16 October 2014 19:10, David Groppe <david.m.groppe at gmail.com> wrote:

>
> You can still use ICA with so few channels for artifact rejection, Becky.
> It should successfully extract large artifacts like blinks and eye
> movement.
>    cheers,
>       -D
>
> On Thu, Oct 16, 2014 at 10:49 AM, Becky Prince <becky.prince at york.ac.uk>
> wrote:
>
>> Dear List,
>>
>> I'm working on a frequency analysis of resting EEG with relatively few
>> channels (6 scalp, 2 mastoids, 2 EOGs), and I'd like to be able to extract
>> reliable estimates of low frequency power.  In previous analyses I have
>> used ICA to remove artifacts, but this was with 64-channel data.  Has
>> anyone used ICA for artifact removal with a low-density channel array, or
>> could anyone recommend resources on pipelines for this type of data and
>> analysis?
>>
>> If ICA can't be used with this data, then I suppose the alternative is to
>> remove segments containing artifacts, and then only analyse the remaining
>> segments that are long enough to extract an estimate of the lowest
>> frequency (e.g. ~1.5 seconds for a minimum frequency of 2 Hz).  Is this
>> correct, or is there a better approach?
>>
>> Sorry that this is not strictly an EEGLAB question.  I am doing the
>> analysis in EEGLAB so any EEGLAB-specific tips would be appreciated!
>>
>> Thanks,
>> Becky
>> ____________________________________________
>>
>> Becky Gilbert (nee Prince)
>> PhD Researcher
>>
>> http://www.york.ac.uk/psychology/staff/postgrads/becky.gilbert/
>> Lab C120
>> Department of Psychology
>> University of York
>> Heslington, York, YO10 5DD, UK
>>
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>
>
>
> --
> David Groppe, Ph.D.
> Laboratory for Multimodal Human Brain Mapping
> Feinstein Institute for Medical Research
> Manhasset, New York
> http://www.cogsci.ucsd.edu/~dgroppe/
>
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