<html><head><style>body{font-family:Helvetica,Arial;font-size:13px}</style></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div id="bloop_customfont" style="font-family:Helvetica,Arial;font-size:13px; color: rgba(0,0,0,1.0); margin: 0px; line-height: auto;"><div id="bloop_customfont" style="margin: 0px;">Hi Matthias,</div><div id="bloop_customfont" style="margin: 0px;"><br></div><div id="bloop_customfont" style="margin: 0px;">If you want to regress out single-trial variance that's explained by head motion see this tutorial: http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis, I think it's equally valid to do this at the sensor vs source level.</div><div id="bloop_customfont" style="margin: 0px;"><br></div><div id="bloop_customfont" style="margin: 0px;">Another method that is described in Stolk et al http://www.ncbi.nlm.nih.gov/pubmed/23246857 and originally Uutela et al http://www.ncbi.nlm.nih.gov/pubmed/11707098 is to incorporate changes in the grad structure into you source reconstruction procedure.</div><div id="bloop_customfont" style="margin: 0px;"><br></div><div id="bloop_customfont" style="margin: 0px;">This is implemented in ft_headmovement, but I've personally not found it very intuitive to use - perhaps one of the authors could elaborate? Perhaps it's worth adding a short section on the wiki on this..</div><div><br></div><div>Cheers,</div></div> <div id="bloop_sign_1443123317041593088" class="bloop_sign"><div style="font-family:helvetica,arial;font-size:13px"><div>— </div><div><span style="font-family: 'helvetica Neue', helvetica;">Anne E. Urai, MSc</span></div><div><span style="font-family: 'helvetica Neue', helvetica;">PhD student | Institut für Neurophysiologie und Pathophysiologie </span></div><div><span style="font-family: 'helvetica Neue', helvetica;">Universitätsklinikum Hamburg-Eppendorf | </span><span style="font-family: 'helvetica Neue', helvetica;">Martinistrasse 52, 20246 | Hamburg, Germany </span></div><div><span style="font-family: 'helvetica Neue', helvetica;"><a href="http://www.anneurai.net">www.anneurai.net</a> </span></div></div></div> <br><p class="airmail_on" style="color:#000;">On 24 Sep 2015 at 14:46:34, Fritsche, M. (Matthias) (<a href="mailto:m.fritsche@student.ru.nl">m.fritsche@student.ru.nl</a>) wrote:</p> <blockquote type="cite" class="clean_bq"><span><div><div></div><div>Dear Fieldtrippers,<br><br>I started looking into offline head movement correction of MEG data wondered about the following:<br>Is it possible/sensible to correct time-courses of source reconstructed data for head movement (that is timepoint-by-timepoint for individual sources)?<br><br>The GLM approach with ft_regressconfound only computes trial-by-trial power estimates, whose variance due to head movement is removed, right? Is there a theoretical consideration that renders the timepoint-by-timepoint correction for individual sources pointless? Or is there maybe a technical limitation, e.g. in terms limited computation resources?<br><br>I couldn’t find any information on this on the wiki, or the mailing list archive. Please excuse if I should have overlooked something or if this is a silly question.<br><br>Best,<br>Matthias<br><br><br>_______________________________________________<br>fieldtrip mailing list<br>fieldtrip@donders.ru.nl<br>http://mailman.science.ru.nl/mailman/listinfo/fieldtrip</div></div></span></blockquote></body></html>