<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">Hi Robert,<div class=""><br class=""></div><div class=""><div><blockquote type="cite" class=""><div class=""><div class=""><div style="font-family:Helvetica Neue, Helvetica, Arial, sans-serif;font-size:small;" class=""><div class="">The Australian data was analyzed by two scientists/clinicians in the audience of a workshop that I was doing in 2014 and they are the ones that did the ICA component selection using commercial WinEEG software and not me.</div></div></div></div></blockquote><div><br class=""></div><div>Most commercial EEG software preprocess the data using PCA to reduce the dimensionality of the data. The idea behind this is that users should not have to go through as many components as channels. It is easier to have them select components within 5 or 10 exemplars. However this PCA dimension reduction can bias the reconstruction (we have data to back this up but it is not published yet).</div><div><br class=""></div><div>However, I do not think PCA dimension reduction before running ICA was responsible for what you observed (because your data is very clean and even after PCA and the 2 artifact components have huge contribution to the data variance, you would get very similar components). I think the WinEEG users simply did not select the correct artifact components, or maybe WinEEG failed to implement ICA correctly.</div><br class=""><blockquote type="cite" class=""><div class=""><div style="font-family:Helvetica Neue, Helvetica, Arial, sans-serif;font-size:small;" class=""><div class="">You are welcome to download NeuroGuide and install and launch and then paste the key A into an email to me. I have posted a tutorial on our webpage but I can create a better tutorial to reduce the learning curve. Similarly when I am able to concentrate on EEGlab then you can tutor me to reduce my learning curve. Here is a url to the download webpage:</div><div class=""><a href="http://www.appliedneuroscience.com/Download_NeuroGuide.htm" rel="nofollow" target="_blank" class="">http://www.appliedneuroscience.com/Download_NeuroGuide.htm</a><br class=""></div><div class=""><br class=""></div><div class="">At the end of the day together lets find ways to use the full power of ICA to explore network dynamics which is my favorite topic and also one that future science depends on.</div></div></div></blockquote><div><br class=""></div><div>Yes, I agree on that view. Exploring network dynamics with ICA is not an easy topic. The trend these days is not to use ICA for connectivity analysis but instead define regions of interest and compute pairwise connectivity between all brain regions as in this recent paper <a href="https://www.ncbi.nlm.nih.gov/pubmed/28300640" class="">https://www.ncbi.nlm.nih.gov/pubmed/28300640</a>. What can be done is to use ICA components to define these regions and compute activity in these regions. It is an open area of research.</div><div><br class=""></div><div>Best wishes,</div><div><br class=""></div><div>Arno</div><br class=""><blockquote type="cite" class=""><div class=""><div style="font-family:Helvetica Neue, Helvetica, Arial, sans-serif;font-size:small;" class=""><div class=""><br class=""></div><div class="">Best regards,</div><div class=""><br class=""></div><div class="">Robert</div><div class=""><br class=""></div><div class=""><br class=""></div><div id="yahoo_quoted_8079598956" class="yahoo_quoted"><div style="font-family:'Helvetica Neue', Helvetica, Arial, sans-serif;font-size:13px;color:#26282a;" class=""><div class="">On Wednesday, June 14, 2017, 4:40:43 PM EDT, Arnaud Delorme <<a href="mailto:arno@ucsd.edu" class="">arno@ucsd.edu</a>> wrote:</div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><div id="yiv3713204255" class=""><div class="">Dear Robert,<div class="yiv3713204255"><br clear="none" class="yiv3713204255"></div><div class="yiv3713204255">There does seem to be a phase difference in your powerpoint. However, it is important to know which ICA component you removed to understand why this is the case. Are you sure these were artifactual components? Removing brain components may alter the phase of the signal recorded on the scalp (it would be as if you were removing from the scalp signal the contribution of a brain area). Without that information, it is not possible to figure out the origin of the phase difference. </div><div class="yiv3713204255"><br clear="none" class="yiv3713204255"></div><div class="yiv3713204255">This seems to be the same data you shared yesterday. I have looked at it. Black is before ICA and red after removing the 2 eye components. You can see that there is no phase shift at 102.43 second after I remove the two artifactual ICA components. I have provided the code in my email yesterday if you want to reproduce this result in EEGLAB.</div><div class="yiv3713204255"><br clear="none" class="yiv3713204255"></div><div class="yiv3713204255">Best wishes,</div><div class="yiv3713204255yqt2408029934" id="yiv3713204255yqtfd77854"><div class="yiv3713204255"><br clear="none" class="yiv3713204255"></div><div class="yiv3713204255">Arno</div></div><div class="yiv3713204255"><br clear="none" class="yiv3713204255"></div><div class="yiv3713204255"><span id="cid:Pmo1wHA1DZbcYxO7KQNn"><ICA_phase_example.png></span></div><div class="yiv3713204255"><br clear="none" class="yiv3713204255"><div class=""><blockquote class="yiv3713204255" type="cite"><div class="yiv3713204255">On Jun 14, 2017, at 11:14 AM, Robert Thatcher <<a rel="nofollow" shape="rect" class="yiv3713204255" ymailto="mailto:rwthatcher2@yahoo.com" target="_blank" href="mailto:rwthatcher2@yahoo.com">rwthatcher2@yahoo.com</a>> wrote:</div><br clear="none" class="yiv3713204255Apple-interchange-newline"><div class="yiv3713204255"><span class=""><Example of Phase Differences at 1min & 46 seconds.pptx></span></div></blockquote></div><div class="yiv3713204255yqt2408029934" id="yiv3713204255yqtfd54385"><br clear="none" class="yiv3713204255"></div></div></div></div></div></div></div></div></div><span id="cid:Pmo1wHA1DZbcYxO7KQNn"><ICA_phase_example.png></span></blockquote></div><br class=""></div></body></html>