<div dir="ltr">Dear Nancy,<div><br></div>> And Matt, I agree that EEGLAB is performing the time frequency transform prior to trial averaging. However, it is my understanding that this gives us the total power, including both phase-locked (evoked) and non-phase locked (induced) activity combined together. I was wondering how to specifically get the values for the induced activity, which it seems would involve a subtraction of total power minus evoked power. <div class="gmail_extra"><br></div><div class="gmail_extra">Something like ERSP after ERP subtracted data to compute specifically non-phase-locked oscillatory power? You probably need to do this ERP subtraction manually then apply newtimef().</div><div class="gmail_extra"><br></div><div class="gmail_extra">We don't do this ERP subtraction by default, except for SIFT.</div><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div><div class="gmail_extra"><br></div><div class="gmail_extra"><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Jan 25, 2017 at 6:56 PM, Lundin, Nancy B. <span dir="ltr"><<a href="mailto:nlundin@indiana.edu" target="_blank">nlundin@indiana.edu</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 dir="ltr" style="font-size:12pt;color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;background-color:rgb(255,255,255)">
<p>Hello Makoto and Matt,<br>
</p>
<p><br>
</p>
<p>Makoto, actually my question was related specifically to calculating induced/non-phase locked activity rather than dealing with ERSP in general. </p>
<p><br>
</p>
<p>And Matt, I agree that EEGLAB is performing the time frequency transform prior to trial averaging. However, it is my understanding that this gives us the total power, including both phase-locked (evoked) and non-phase locked (induced) activity combined together.
I was wondering how to specifically get the values for the induced activity, which it seems would involve a subtraction of total power minus evoked power. <br>
</p>
<p><br>
</p>
<p>One suggestion I have received is to subtract the average ERP in the time domain from the data of each individual trial in the time domain, and then run a wavelet decomposition on this data to get the induced activity. I will try this unless anyone has any
other suggestions. <br>
</p>
<p><br>
</p>
<p>Thank you for your time,<br>
</p><span class="gmail-">
<p>Nancy<br>
</p>
<p><br>
</p>
<div id="gmail-m_5845012144846215253Signature">
<div name="divtagdefaultwrapper">
<b><font face="Times New Roman, Times, serif">Nancy Lundin</font></b>
<div><b><font face="Times New Roman, Times, serif" size="2">Doctoral Student, Clinical Psychology & Neuroscience</font></b></div>
<div><font face="Times New Roman, Times, serif" size="2">Indiana University Bloomington</font></div>
<div><font face="Times New Roman, Times, serif" size="2">Department of Psychological & Brain Sciences</font></div>
<div><font face="Times New Roman, Times, serif" size="2">1101 East 10th St.</font></div>
<div><font face="Times New Roman, Times, serif" size="2">Bloomington, IN 47405</font></div>
</div>
</div>
</span><div style="color:rgb(33,33,33)">
<hr style="display:inline-block;width:98%">
<div id="gmail-m_5845012144846215253divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>From:</b> matt schalles <<a href="mailto:matt.schalles@gmail.com" target="_blank">matt.schalles@gmail.com</a>><br>
<b>Sent:</b> Wednesday, January 25, 2017 8:45 PM<br>
<b>To:</b> <a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a><br>
<b>Cc:</b> Lundin, Nancy B.; <a href="mailto:eeglablist@sccn.ucsd.edu" target="_blank">eeglablist@sccn.ucsd.edu</a><br>
<b>Subject:</b> Re: [Eeglablist] Induced power from wavelet</font>
<div> </div>
</div><div><div class="gmail-h5">
<div>
<div dir="ltr">
<div>
<div>Hi Nancy, et al. <br>
<br>
It is my understanding that the way EEGlab calculates ERSPs, the time-frequency transform is done prior to temporal averaging of trials, which should give you the induced activity, without having to do additional subtractions.<br>
<br>
</div>
<div>cheers,<br>
</div>
</div>
</div>
<div class="gmail_extra"><br clear="all">
<div>
<div class="gmail-m_5845012144846215253gmail_signature">
<div dir="ltr">
<div>
<div dir="ltr">
<div>
<div dir="ltr">Matt Schalles, Ph.D.
<div><font size="1">Cognitive Neuroscientist, VA Health System<br>
</font></div>
<div><font size="1">Visiting Assistant Professor, Mills College<br>
</font></div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<br>
<div class="gmail_quote">On Tue, Jan 24, 2017 at 6:00 PM, 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:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<div dir="ltr">Dear Nancy,
<div><br>
</div>
<div>I don't quite understand the question, but I guess that you want to know how you deal with ERSP most straightforwardly? I think you use newtimef() function, and visualize the first output as </div>
<div><br>
</div>
<div>figure</div>
<div>imagesc(output); axis xy</div>
<div><br>
</div>
<div>The basic figure is this. Then you change xaxis labels, yaxis labels, etc. Do not forget to use eegh(); you perform an operation from GUI first, then type eegh() to obtain the code executed.</div>
<div><br>
</div>
<div>Makoto</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">
<div>
<div class="gmail-m_5845012144846215253h5">On Sun, Jan 22, 2017 at 3:01 PM, Lundin, Nancy B. <span dir="ltr">
<<a href="mailto:nlundin@indiana.edu" target="_blank">nlundin@indiana.edu</a>></span> wrote:<br>
</div>
</div>
<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>
<div class="gmail-m_5845012144846215253h5">
<div dir="ltr" style="font-size:12pt;color:rgb(0,0,0);font-family:calibri,arial,helvetica,sans-serif;background-color:rgb(255,255,255)">
<p>Hello list,<br>
</p>
<p><br>
</p>
<p>I would like to calculate the induced ERSP in my data. I planned to run the wavelet decomposition on my data to calculate total power, and then separately run a wavelet over the averaged data to get the evoked activity, and then subtract the evoked from
the total to get induced activity. However, when I manually average the trials, I get an error message when attempting to save my EEG datasets saying that the number of epochs in the data structure is not the same as the number of epochs in the data (which
makes sense, since I averaged).<br>
</p>
<p><br>
</p>
<p>I was wondering if there was a more direct way to calculate induced ERSP in EEGLAB rather than this manual subtraction method? <br>
</p>
<p><br>
</p>
<p>Thank you,<br>
</p>
<p>Nancy<br>
</p>
<p><br>
</p>
<div id="gmail-m_5845012144846215253m_-1334671888514428889m_-3555470604473295485Signature">
<div name="divtagdefaultwrapper"><b><font face="Times New Roman, Times, serif">Nancy Lundin</font></b>
<div><b><font size="2" face="Times New Roman, Times, serif">Doctoral Student, Clinical Psychology & Neuroscience</font></b></div>
<div><font size="2" face="Times New Roman, Times, serif">Indiana University Bloomington</font></div>
<div><font size="2" face="Times New Roman, Times, serif">Department of Psychological & Brain Sciences</font></div>
<div><font size="2" face="Times New Roman, Times, serif">1101 East 10th St.</font></div>
<div><font size="2" face="Times New Roman, Times, serif">Bloomington, IN 47405</font></div>
</div>
</div>
</div>
<br>
</div>
</div>
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<div class="gmail-m_5845012144846215253m_-1334671888514428889gmail_signature">
<div dir="ltr">Makoto Miyakoshi<br>
Swartz Center for Computational Neuroscience<br>
Institute for Neural Computation, University of California San Diego<br>
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</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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