<div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr">Dear Panos,<br><br>Welcome to the time-frequency world.<br><br>> Would I just need to bandpass filter my post-processed EEG signal to each frequency range of interest (i.e., alpha: 8-12Hz etc) and then plot the remaining EEG signal over time, or is there another way to do this?<br><div><br></div><div>That's one way to go. Nothing is wrong with that!</div><div><br></div><div>More convenient and established way to go is to perform time-frequency transform using short-term Fourier transform or Wavelet transform. Google EEGLAB time-frequency and you'll find many of our past workshop materials. For example, see Slide 21 of this file</div><div><a href="https://sccn.ucsd.edu/mediawiki/images/a/a6/C2_A3_Time-frequencyDecAndAdvancedICAPracticum_updateJan2017.pdf">https://sccn.ucsd.edu/mediawiki/images/a/a6/C2_A3_Time-frequencyDecAndAdvancedICAPracticum_updateJan2017.pdf</a><br></div><div><br></div><div>You can also obtain bin-mean values from power spectral density. See below. </div><div><a href="https://sccn.ucsd.edu/wiki/Makoto's_useful_EEGLAB_code#How_to_extract_EEG_power_of_frequency_bands">https://sccn.ucsd.edu/wiki/Makoto's_useful_EEGLAB_code#How_to_extract_EEG_power_of_frequency_bands</a><br></div></div></div><div dir="ltr"><br></div><div>Makoto</div><br><div class="gmail_quote"><div dir="ltr">On Mon, Jan 7, 2019 at 1:34 AM Fotiadis, Panagiotis <<a href="mailto:Panagiotis.Fotiadis@pennmedicine.upenn.edu">Panagiotis.Fotiadis@pennmedicine.upenn.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
<div dir="ltr">
<div id="gmail-m_-5825005070605991825divtagdefaultwrapper" dir="ltr" style="font-size:12pt;color:rgb(0,0,0);font-family:Calibri,Helvetica,sans-serif,Helvetica,EmojiFont,"Apple Color Emoji","Segoe UI Emoji",NotoColorEmoji,"Segoe UI Symbol","Android Emoji",EmojiSymbols">
<p style="margin-top:0px;margin-bottom:0px">Hello,</p>
<p style="margin-top:0px;margin-bottom:0px"><br>
</p>
<p style="margin-top:0px;margin-bottom:0px">I am fairly new to EEGLab and I had a question concerning the deconstruction of my EEG signal into its alpha/beta/theta/delta sub-components:</p>
<p style="margin-top:0px;margin-bottom:0px"><br>
</p>
<p style="margin-top:0px;margin-bottom:0px">After pre-processing some subjects with EEG data from 128 channels and performing ICA (using runica), I used eeglab and chronux to plot the power/frequency and frequency/time spectrograms of several epochs of interest. </p>
<p style="margin-top:0px;margin-bottom:0px"><br>
</p>
<p style="margin-top:0px;margin-bottom:0px">Is there a way to extract the alpha/beta/theta/delta frequencies of those epochs and quantify when they occur in time? I can visualize when each type of neuronal oscillation occurs by looking at the overall frequency/time spectrogram,
but I was wondering whether there was a more robust way to actually plot each type of oscillation separately and/or quantify when it occurs.</p>
<p style="margin-top:0px;margin-bottom:0px"><br>
</p>
<p style="margin-top:0px;margin-bottom:0px">Would I just need to bandpass filter my post-processed EEG signal to each frequency range of interest (i.e., alpha: 8-12Hz etc) and then plot the remaining EEG signal over time, or is there another way to do this?</p>
<p style="margin-top:0px;margin-bottom:0px"><br>
</p>
<p style="margin-top:0px;margin-bottom:0px">Thank you in advance!</p>
<p style="margin-top:0px;margin-bottom:0px"><br>
</p>
<p style="margin-top:0px;margin-bottom:0px">Best,</p>
<p style="margin-top:0px;margin-bottom:0px">Panos</p>
</div>
</div>
_______________________________________________<br>
Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html" rel="noreferrer" target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>
To unsubscribe, send an empty email to <a href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu" target="_blank">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>
For digest mode, send an email with the subject "set digest mime" to <a href="mailto:eeglablist-request@sccn.ucsd.edu" target="_blank">eeglablist-request@sccn.ucsd.edu</a></blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" 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></div></div>