<div dir="ltr">Dear Brittany,<div><br></div><div>The trimOutlier() plugin can let you 'trim' the outliers i.e., cut out the window for rejection. Some people say this is simple and good way to go to 'clean' your data. However, if you have so many single-channel artifacts, because this method will reject a chunk across all the channels, you may end up with too much data rejection. If this is an issue, use clean_rawdata() plugin. This plugin as artifact subspace rejection (ASR) algorithm. For more info, see the link below.</div><div><a href="https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline#Alternatively.2C_cleaning_continuous_data_using_ASR_.2803.2F16.2F2018_updated.29">https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline#Alternatively.2C_cleaning_continuous_data_using_ASR_.2803.2F16.2F2018_updated.29</a><br></div><div><br></div><div>I like ASR because it is less wasteful. For trying it out, start with SD == 20 for ASR parameter ('Repair burst' part).</div><div><br></div><div>Makoto</div></div><br><div class="gmail_quote"><div dir="ltr">On Fri, Jul 6, 2018 at 12:05 PM Brittany Alperin <<a href="mailto:balperin07@gmail.com">balperin07@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Thanks Makato<div><br></div><div>If I do find outliers, is there anything I can do about it? Any idea what types of things would cause this in the data? </div><div><br></div><div>Thanks,</div><div>Brittany</div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, Jul 6, 2018 at 11:57 AM, Makoto Miyakoshi <span dir="ltr"><<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Dear Brittany,<div><br></div><div>The speed of Infomax implemented in runica() does get affected by data quality.</div><div>I recommend you check data data set using trimOutlier() plugin.</div><div><a href="https://sccn.ucsd.edu/wiki/TrimOutlier" target="_blank">https://sccn.ucsd.edu/wiki/TrimOutlier</a><br></div><div>Go back to the continuous data and run trimOutlier. It will show you envelope of all channels across time. Well-tempered data should show 'stationary' (i.e., the envelope shapes more or less rectangular with constant width) shape. If you have super huge outlier or continuous zeros, you will easily find it. Such outliers can make the infomax really slow.</div><div><br></div><div>Makoto</div><br><div class="gmail_quote"><div><div class="m_4918249864590132933h5"><div dir="ltr">On Fri, Jul 6, 2018 at 10:31 AM Brittany Alperin <<a href="mailto:balperin07@gmail.com" target="_blank">balperin07@gmail.com</a>> wrote:<br></div></div></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div><div class="m_4918249864590132933h5"><div dir="ltr">Hello<div><br></div><div>I'm currently working with a fairly large dataset and the ICA takes several hours to run, which I consider normal. I have one file, which is seemingly no different from the others, but the ICA has been running for ~40 hours and it's not even half way done.</div><div><br></div><div>I've had this happen with different datasets before, but it's fairly rare so I never thought much of it until now.</div><div><br></div><div>Has anyone had this happen? Any thoughts? I'm using EEGLAB 12.0.2.6b, Matlab 2012b, and a Windows 7 Enterprise OS.</div><div><br></div><div>Thanks,</div><div>Brittany</div><div><br></div><div>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><a name="m_4918249864590132933_m_8212527338899718857_m_-7345612886871105316__MailAutoSig"><b><span>Brittany Alperin<span></span></span></b></a></p>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><span><span>PhD Candidate<span></span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><span><span>ATTEND LAB<span></span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><span><span>Department of Behavioral Neuroscience<span></span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><span><span>Oregon Health & Science University<span></span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><span><span>Portland, OR<span></span></span></span></p>
<p class="MsoNormal" style="margin:0in 0in 0.0001pt;font-size:11pt;font-family:Calibri,sans-serif"><span><span>503-418-8402<span></span></span></span></p>
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</blockquote></div><br></div>
</blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="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>