<div dir="ltr">Dear Makoto,<div><br></div><div>Many thanks for your reply. At one time I did see ghost signals (even scarier than those on the wiki page) when I didn't remove a channel after re-referencing. Indeed this is profound to me, but thank you again for your suggestions. </div><div><br></div><div>Best regards,</div><div><br></div><div>Paul</div><div><br></div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">2014-11-16 23:21 GMT+01:00 Makoto Miyakoshi <span dir="ltr"><<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><span class="">> If I just rereference after ICA, would ICA-matrix transformation also take care of the data rank issue or should I still discard 1 channel? <br><div class="gmail_extra"><br></div></span><div class="gmail_extra">Sometimes it does, sometimes not. Therefore I would say it does not. When we got the weird results shown in that wiki page I directed, even Scott did not know what was going on. In order to avoid this kind of confusion I recommend you reject a channel. You can alternatively use pca option to reduce the rank, but it is less straightforward in my opinion. I believe we should simplify the data as much as possible, so remove any potential source of later confusion.</div><span class="HOEnZb"><font color="#888888"><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div></font></span><div><div class="h5"><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Nov 5, 2014 at 12:29 AM, Paul Yu-Chun Chang <span dir="ltr"><<a href="mailto:Y.Chang@lipp.lmu.de" target="_blank">Y.Chang@lipp.lmu.de</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr">Dear Arno & Makoto,<div><br></div><div>Many thanks for your reply and the suggested pages; they are indeed very helpful. One small question I still have, then, is that it is suggested in Makoto's page to discard (any) 1 channel from the data at the step of average-rereferencing (due to reduction of data rank by 1), before running ICA. If I just rereference after ICA, would ICA-matrix transformation also take care of the data rank issue or should I still discard 1 channel? </div><div><br></div><div>Thank you very much,</div><div><br></div><div>Paul</div></div><div><div><div class="gmail_extra"><br><div class="gmail_quote">2014-11-05 9:03 GMT+01:00 Arnaud Delorme <span dir="ltr"><<a href="mailto:arno@ucsd.edu" target="_blank">arno@ucsd.edu</a>></span>:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div style="word-wrap:break-word">There is also this page just in case. <div><br></div><div><a href="http://sccn.ucsd.edu/wiki/Quick_Rejection_Tutorial" target="_blank">http://sccn.ucsd.edu/wiki/Quick_Rejection_Tutorial</a></div><div><br></div><div>Makoto, I have slightly edited your new page.<div><div><span><br><blockquote type="cite"><div dir="ltr"><div><div>> 2. When and how to perform re-referencing:</div><div>It seems I should re-reference to average before ICA, but there seems to be some counterarguments, too:</div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008309.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008309.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2003/000090.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2003/000090.html</a><br></div><div><br></div><div>Just re-reference to the average reference. Don't forget to reject one channel after this.</div></div></div></blockquote><div><br></div></span><div>Yes, I would reference to average reference before running ICA as well although this is not critical (you can always rereference after running ICA and this will transform the ICA matrix as well). After running ICA for years, it seems that decomposition using the average reference are slightly better. However, there is no formal comparison I know of. In theory, since it is all linear, it will not change anything for ICA (although because of numerical implementation it might).</div><span><br><blockquote type="cite"><div dir="ltr"><div><div>> I'm not pretty sure whether to include EOG channels either, as there seems to be pros and cons: </div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2007/001801.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2007/001801.html</a></div></div><div><br></div><div>Do include EOG channels for ICA. I made a wrong answer last time.</div></div></blockquote><div><br></div></span><div>I would include the EOG channels if you recorded them with the same reference as ICA. Otherwise do not include them.</div><div><br></div><div>Hope this helps,</div><div><br></div><div>Arno</div><div><div><div><br></div><br><blockquote type="cite"><div dir="ltr"><div><br></div><div>Makoto</div><div class="gmail_extra"><br><div class="gmail_quote">On Sat, Oct 25, 2014 at 2:54 AM, Paul Yu-Chun Chang <span dir="ltr"><<a href="mailto:Y.Chang@lipp.lmu.de" target="_blank">Y.Chang@lipp.lmu.de</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr"><div>Dear All,</div><div><br></div><div>I have 32-channel Neuroscan recordings (ca. 1 hr per subject) and am recently trying to use ICA to remove blinks and eye movements from the data (EEGLAB version 12.0.2.4b). After checking out some relevant discussions/wiki pages/tutorials I find myself however still a bit confused (particularly regarding re-referencing, baseline correction, and channels to be included when running ICA) and am having some further questions. I'd really appreciate your help.</div><div><br></div><div>Some essential steps as I understand now involve (pls correct me if I'm wrong):</div><div><br></div><div>1. Reject bad epochs/channels to prune the data.</div><div>(source: <a href="http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA" target="_blank">http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA</a> ; <a href="http://sccn.ucsd.edu/eeglab/workshop06/handout/Practicum_3_ICA_Process.pdf" target="_blank">http://sccn.ucsd.edu/eeglab/workshop06/handout/Practicum_3_ICA_Process.pdf</a>)</div><div>2. Train ICA firstly on 1 Hz high-pass filtered pruned dataset.<br></div><div>3. Apply ICA weights to the same subject's 0.1 Hz high-pass filtered data and evaluate components.</div><div>(source: <a href="http://sccn.ucsd.edu/pipermail/eeglablist/2011/004424.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2011/004424.html</a>)</div><div>4. Interpolate bad channels.<br></div><div><br></div><div>I'm however not so clear about:</div><div><br></div><div>1. When to perform base-line correction: <br></div><div>It seems most people suggest not to do it before ICA training based on Groppe's 'split-half' paper: </div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2010/003080.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2010/003080.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html</a><br></div><div>But there are some counterarguments:</div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2012/005513.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2012/005513.html</a><br></div><div>So I guess it's still better to do it after ICA?</div><div><br></div><div>2. When and how to perform re-referencing:</div><div>It seems I should re-reference to average before ICA, but there seems to be some counterarguments, too:</div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008309.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008309.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2003/000090.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2003/000090.html</a><br></div><div><br></div><div>I'm not pretty sure whether to include EOG channels either, as there seems to be pros and cons: <br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html</a><br></div><div><a href="http://sccn.ucsd.edu/pipermail/eeglablist/2007/001801.html" target="_blank">http://sccn.ucsd.edu/pipermail/eeglablist/2007/001801.html</a></div><div><br></div><div>Also is it all right to use average of M1/M2 (mastoid sites) for re-referencing instead? Should M1/M2 be included for ICA training?</div><div><br></div><div>Many thanks!</div><span><font color="#888888"><div><br></div><div>Paul</div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><br><br clear="all"><div><br></div>-- <br><div dir="ltr"><br style="color:rgb(136,136,136)"><div dir="ltr" style="color:rgb(136,136,136)"><div><span style="color:rgb(68,68,68)"><div>Paul Yu-Chun Chang</div><div>Graduate School Language & Literature Munich - Class of Language</div><div>Ludwig-Maximilians-Universität München</div><div>Schellingstraße 10</div><div>80799 München, Deutschland</div><div>Email: <a href="mailto:Y.Chang@lipp.lmu.de" target="_blank">Y.Chang@lipp.lmu.de</a></div></span></div></div></div></font></span></div>
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_______________________________________________<br>Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html" target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>To unsubscribe, send an empty email to <a href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu" target="_blank">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" target="_blank">eeglablist-request@sccn.ucsd.edu</a></blockquote></div></div></div><br></div></div></div></blockquote></div><br><br clear="all"><div><br></div>-- <br><div><div dir="ltr"><br style="color:rgb(136,136,136)"><div dir="ltr" style="color:rgb(136,136,136)"><div><span style="color:rgb(68,68,68)"><div>Paul Yu-Chun Chang</div><div>Graduate School Language & Literature Munich - Class of Language</div><div>Ludwig-Maximilians-Universität München</div><div>Schellingstraße 10</div><div>80799 München, Deutschland</div><div>Email: <a href="mailto:Y.Chang@lipp.lmu.de" target="_blank">Y.Chang@lipp.lmu.de</a></div></span></div></div></div></div>
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</div></div></blockquote></div><br><br clear="all"><div><br></div>-- <br><div><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div></div>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><div dir="ltr"><br style="color:rgb(136,136,136)"><div dir="ltr" style="color:rgb(136,136,136)"><div><span style="color:rgb(68,68,68)"><div>Paul Yu-Chun Chang</div><div>Graduate School Language & Literature Munich - Class of Language</div><div>Ludwig-Maximilians-Universität München</div><div>Schellingstraße 10</div><div>80799 München, Deutschland</div><div>Email: <a href="mailto:Y.Chang@lipp.lmu.de" target="_blank">Y.Chang@lipp.lmu.de</a></div></span></div></div></div></div>
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