<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Thanks for the plug Grega! I would be interested as well.<div><br></div><div>In case it would be of help:</div><div><br></div><div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal normal normal 12px/normal Times; ">Dien, J. (2010). The ERP PCA Toolkit: An Open Source Program For Advanced Statistical Analysis of Event Related Potential Data. <i>Journal of Neuroscience Methods</i>, <i>187</i>(1), 138-145.</div></div><div><br></div><div><a href="http://sourceforge.net/projects/erppcatoolkit/">http://sourceforge.net/projects/erppcatoolkit/</a></div><div><br></div><div>Cheers!</div><div><br></div><div>Joe</div><div><br></div><div><br><div><div>On Sep 28, 2010, at 1:14 PM, Grega Repovs wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><div style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div>Dear Rob & Hugh,</div><div><br></div>Since there seem to be arguments against using the problematic channels both before as well as after interpolation, why not run ICA without those channels. So the procedure would be:<div><br></div><div>1/ Identify and remove bad channels</div><div>2/ Perform ICA on good channels only</div><div>3/ Remove bad ICA components</div><div>4/ Reconstruct good channels</div><div>5/ Interpolate bad channels</div><div><br></div><div>This way neither noise nor non-linearities would affect the ICA solution and bad channels can still be interpolated based on cleaned data.</div><div><br></div><div>I also have one other question with regards to FASTER. In your paper you compared it to SCADS. I was wondering, why did you not compare it to ERP PCA Toolkit by Joseph Dien, which also performs fully automated data preprocessing and employs algorithms similar to FASTER. I myself would be quite interested in that comparison.</div><div><br></div><div><div>All the best,</div><div><br></div><div>Grega Repovs</div></div><div><br><div><br></div><div><br><div><div>On Sep 28, 2010, at 12:04 PM, Robert Whelan wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><p style="margin-bottom: 0cm;"><font><font size="2">Jordi Costa Faidella wrote "</font></font>Is it correct to
perform an ICA on a dataset in which some of the channels have been
interpolated?"<br>
</p><p style="margin-bottom: 0cm;"><font><font size="2">This is an interesting question and we considered both orders
(each order has some advantages and disadvantages) for the FASTER
method. Ultimately, we decided to run interpolation first followed ICA.
Here was our rationale:<br>
</font></font></p><p style="margin-bottom: 0cm;"><font><font size="2">As the EEGLAB manual recommends – “ICA works best when given
a large amount of basically similar and mostly clean data.” (see p.59).
Therefore, an ICA on a dataset in which some channels are noisy
(perhaps with a lot of non-stereotypic data due to a problem with the
electrode) may decrease the quality of the ICA (i.e., dissimilar
activations are mixed into the ICs).</font></font></p><p style="margin-bottom: 0cm;"><font><font size="2">On the other hand, interpolating before ICA raises a couple
of issues 1) it reduces the dimensionality of the data and 2)
introduces some non-linearity into the data (if the interpolation
method was not linear), which is detrimental to the ICA solution. We
dealt with Issue 1in FASTER by restricting the maximum number of ICs to
correspond with the reduced rank of the data after interpolation.</font></font></p><p style="margin-bottom: 0cm;"><font><font size="2">The choice then was between reducing the quality of the ICA
by introducing noisy channels or reducing the quality of the ICA by the
non-linearity introduced due to spherical interpolation. </font></font><font><font size="2">Although ICA assumes
linearity, there is almost certainly some non-linearity in the signals
recorded at the scalp, and the non-linearity introduced by spherical
interpolation is likely only a small contributer to the overall
non-linearity. </font></font><font><font size="2">In any case, based on pilot testing we found that when the
ICA was done with noisy channels included (i.e., not interpolated out)
the resulting components were less useful than when the data were
cleaner (i.e., the channels were interpolated). As an aside, testing
algorithms on real data proved much more informative than testing on
the simulated data, perhaps due to the inclusion of non-stereotypic
artefacts in the real data.</font></font> <br>
</p><p style="margin-bottom: 0cm;"><font><font size="2">That said, we are certainly open to persuasion on this issue </font></font><font><font size="2">and/or
suggestions about how to quantify which order is better</font></font><font><font size="2">. Also, might
there be situations in which one order is superior to the other,
perhaps depending on the maximum number of ICs that can be generated? <br>
</font></font></p><p style="margin-bottom: 0cm;"><font><font size="2">If there is demand, we can also configure FASTER so that the
user can select the order of the processing steps. Email me directly <a href="mailto:robert.whelan@tcd.ie" target="_blank">robert.whelan@tcd.ie</a> or <a href="mailto:whelanrob@gmail.com">whelanrob@gmail.com</a>
if this is something that people might want or with any other
suggestions.<br>
</font></font></p>
<font><font size="2"><br>
Best Regards, <br>
<br>
Rob & Hugh</font></font><br clear="all"><br>-- <br>Robert Whelan, PhD<br>Senior Research Scientist<br><br>Trinity Centre for Bioengineering<br>Trinity College Dublin<br><br>Department of Neurology<br>St. Vincent's University Hospital<br>
Elm Park, Dublin 4<br><br>webpage: <a href="http://www.mee.tcd.ie/~neuraleng/People/Robert">http://www.mee.tcd.ie/~neuraleng/People/Robert</a><br>
_______________________________________________<br>Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>To unsubscribe, send an empty email to <a href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>For digest mode, send an email with the subject "set digest mime" to <a href="mailto:eeglablist-request@sccn.ucsd.edu">eeglablist-request@sccn.ucsd.edu</a></blockquote></div><br></div></div><br><br><div>
<div style="font-size: 12px; "><br class="Apple-interchange-newline">-- </div><div style="font-size: 12px; ">Asist. Prof. Grega Repovš, Ph.D.</div><div style="font-size: 12px; ">Department of Psychology</div><div style="font-size: 12px; ">University of Ljubljana</div><div style="font-size: 12px; ">Aškerčeva 2</div><div style="font-size: 12px; ">SI-1000 Ljubljana</div><div style="font-size: 12px; ">tel: +386 1 241 1175</div><div style="font-size: 12px; ">email: <a href="mailto:grega.repovs@psy.ff.uni-lj.si">grega.repovs@psy.ff.uni-lj.si</a></div>
</div>
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