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<body class='hmmessage'><div dir='ltr'>Dear Jan-Mathjis<div><br><div>Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first.</div><div>I have never done source localization before, but I will try it by going through the extensive FT documentation.</div><div><br></div><div>However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ?</div><div><br></div><div>Regards</div><div>Subbu</div><div><br></div><div><br><div><div id="SkyDrivePlaceholder"></div><hr id="stopSpelling">From: jan.schoffelen@donders.ru.nl<br>Date: Tue, 26 Feb 2013 21:52:37 +0100<br>To: fieldtrip@science.ru.nl<br>Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order<br><br>Dear Subbu,<div><br></div><div>In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. </div><div><br></div><div><br></div><div>Best,</div><div><br></div><div>Jan-Mathijs</div><div><br></div><div><br></div><div><br><div><div>On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote:</div><br class="ecxApple-interchange-newline"><blockquote><span class="ecxApple-style-span" style="border-collapse:separate;font-family:Helvetica;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-align:-webkit-auto;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;font-size:medium;"><div class="ecxhmmessage" style="font-size:12pt;font-family:Calibri;"><div dir="ltr">Dear FieldTrip users<br><br>I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis.<br><br>1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :<a href="http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction" target="_blank">http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction</a>. What would be your opinion ? Is there any article that would shed some light on this ?<br>2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ?<br>3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ?<br><br>Thanks in advance.<div>Subbu</div></div>_______________________________________________<br>fieldtrip mailing list<br><a href="mailto:fieldtrip@donders.ru.nl">fieldtrip@donders.ru.nl</a><br><a href="http://mailman.science.ru.nl/mailman/listinfo/fieldtrip" target="_blank">http://mailman.science.ru.nl/mailman/listinfo/fieldtrip</a></div></span></blockquote></div><br><div>
<span class="ecxApple-style-span" style="border-collapse:separate;color:rgb(0, 0, 0);font-family:Helvetica;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-align:-webkit-auto;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;font-size:medium;"><span class="ecxApple-style-span" style="border-collapse:separate;color:rgb(0, 0, 0);font-family:Helvetica;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-align:-webkit-auto;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;font-size:medium;"><div style="word-wrap:break-word;"><span class="ecxApple-style-span" style="border-collapse:separate;color:rgb(0, 0, 0);font-family:Helvetica;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-align:-webkit-auto;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;font-size:medium;"><div style="word-wrap:break-word;"><span class="ecxApple-style-span" style="border-collapse:separate;color:rgb(0, 0, 0);font-family:Helvetica;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;font-size:medium;"><div style="word-wrap:break-word;"><span class="ecxApple-style-span" style="border-collapse:separate;color:rgb(0, 0, 0);font-family:Helvetica;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;font-size:medium;"><div style="word-wrap:break-word;"><span class="ecxApple-style-span" style="border-collapse:separate;color:rgb(0, 0, 0);font-family:Helvetica;font-size:medium;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;line-height:normal;orphans:2;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;"><div style="word-wrap:break-word;"><div>Jan-Mathijs Schoffelen, MD PhD </div><div><br></div><div>Donders Institute for Brain, Cognition and Behaviour, <br>Centre for Cognitive Neuroimaging,<br>Radboud University Nijmegen, The Netherlands</div><div><br></div><div>Max Planck Institute for Psycholinguistics,</div><div>Nijmegen, The Netherlands</div><div><br></div><div><a href="mailto:J.Schoffelen@donders.ru.nl">J.Schoffelen@donders.ru.nl</a></div><div>Telephone: +31-24-3614793</div></div></span></div></span></div></span></div></span></div></span></span>
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