[Eeglablist] ASR with low density array

[Jonathan Folstein]

Dear eeglab, we are considering using artifact subspace reconstruction for
offline artifact correction/rejection in a mobile EEG experiment. We are
using the cognionics dry mobile EEG cap shown in this video



https://www.youtube.com/watch?v=qYC_3SUxE-M



...but after having read a bit about ASR, there are some potentially
relevant differences between our setup and other things that have been
tried with ASR, e.g. here...



https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline



First, we our montage is not high density – we only have 32 data
electrodes. Second, our approach at the moment is to distribute them
unevenly to cover particular areas of interest – I will try to attach and
image of the montage.  I was wondering if people could weigh  in on the
importance of this to ASR.  For instance, might it be desirable to
distribute the electrodes evenly? Second, are there ballpark opinions about
whether ASR should be used with only 32 electrodes?  Just eyeballing it,
the EEG looks reasonable with the “burst” parameter set to 20, but some
electrodes end up getting removed, leaving us with even fewer electrodes as
inputs to the algorithm. My worry is that this will result in more lossy
corrections since ASR as I understand it relies on correlations between
electrodes.



thanks, and happy holidays



Jonathan


-- 
Jonathan Folstein
Assistant Professor
Department of Psychology
Florida State University
1107 W. Call St.
Tallahassee, FL 32306-4301
office: 850-645-0654
fax: 850-644-7739
folstein at psy.fsu.edu
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