<div dir="ltr">Dear Robert,<div><br></div><div>> Our previous research has shown mu (lack of mu suppression) to have frontal, temporal, central and limbic aspects that are disrupted bilaterally due to multiple connectivity deficits across these regions.<br><div class="gmail_extra"><br></div><div class="gmail_extra">This is interesting. If the mu network is so big, and the EEG sources moves around along with it rather than the entire network 'flashes' in synch, the ICA would return subspaces rather than a single decomposition. We often observe it with occipital alpha.</div><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Mar 17, 2016 at 5:24 AM, robert coben <span dir="ltr"><<a href="mailto:drcoben@gmail.com" target="_blank">drcoben@gmail.com</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 style="word-wrap:break-word">Dave,<div><br></div><div>There is a good reason you are getting multiple components as the mu rhythm is multiply determined and has various aspects. Our previous research has shown mu (lack of mu suppression) to have frontal, temporal, central and limbic aspects that are disrupted bilaterally due to multiple connectivity deficits across these regions. What you see centrally at the surface is the result of these multiple phenomena. So, having multiple components is not a problem to collapse it is the reality of what you are studying.</div><div><br></div><div>Rob</div><div><br><div><blockquote type="cite"><div><div class="h5"><div>On Jan 19, 2016, at 12:33 PM, Jenson, Dave <<a href="mailto:djenson1@uthsc.edu" target="_blank">djenson1@uthsc.edu</a>> wrote:</div><br></div></div><div><div><div class="h5"><div style="font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;direction:ltr;font-family:Tahoma;font-size:10pt">All,<br><br>Does anyone know how to merge components from an ICA decomposition into a single component? I am running a study on the sensorimotor mu rhythm, and I have a few subjects for whom ICA produces multiple potential components. At the moment I am choosing the best component per subject based on scalp map, spectra, and dipole location. However, I still have a few subjects for whom there is no clear winner. I don't want to lose statistical power by excluding a component that represents the sensorimotor mu, but also don't want to disproportionately weight some subjects over others at the study level by including multiple components. Is there a way to 1) merge components or 2) overcome this problem in a different manner?<br><br>-Dave Jenson<br><br></div></div></div><span class=""><span style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;float:none;display:inline!important">_______________________________________________</span><br style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px"><span style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;float:none;display:inline!important">Eeglablist page:<span> </span></span><a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html" style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px" target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px"><span style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;float:none;display:inline!important">To unsubscribe, send an empty email to<span> </span></span><a href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu" style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px" target="_blank">eeglablist-unsubscribe@sccn.ucsd.edu</a><br style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px"><span style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;float:none;display:inline!important">For digest mode, send an email with the subject "set digest mime" to<span> </span></span><a href="mailto:eeglablist-request@sccn.ucsd.edu" style="font-family:Helvetica;font-size:14px;font-style:normal;font-variant:normal;font-weight:normal;letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px" target="_blank">eeglablist-request@sccn.ucsd.edu</a></span></div></blockquote></div><br></div></div><br>_______________________________________________<br>
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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><br></blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail_signature"><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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