<div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small;color:rgb(0,0,255)"><div class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small"><span style="color:rgb(0,0,0)">Hi Alexander, notes below, best wishes.<br></span></div><ul><li><span style="color:rgb(0,0,0)">global field power and FFT (which provides spectral or time-frequency metrics) are not the same.<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small;color:rgb(0,0,255)"> <span style="color:rgb(0,0,0)">GFP is more like a global estimate
across all channels. FFT is a method to get spectral estimates from a
signal (e.g, from single channels, or averaged channels<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">, usually some form of time-series</span>).<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small"> In the case of the article you mentioned it seems like GFP was computed first, and then a spectral estimate.</span></span></span></span></li><li><span style="color:rgb(0,0,0)"><span style="color:rgb(0,0,0)"><span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">If
you google "eeglablist" + your topic, you can find multiple instances
of past responses/discussions about GFP in eeglablist. It is easy to
compute within matlab. However, I don't think there is a GFP function in
eeglab. Within the eeglab distribution, check out the "ft_globalmeanfield" function inside the fieldtrip lite toolbox, which may do the trick for you<br></span></span></span></li><li><span style="color:rgb(0,0,0)"><span style="color:rgb(0,0,0)"><span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">See also for example GFP ERPLAB function mentioned at link below. See documentation for ERPLAB functions mgfperp.m pop_ploterps.m<br></span></span></span></li><li><span style="color:rgb(0,0,0)"><span style="color:rgb(0,0,0)"><span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small"><a href="https://github.com/lucklab/erplab/wiki/EEG-and-ERP-Channel-Operations#example-of-computing-global-field-power">https://github.com/lucklab/erplab/wiki/EEG-and-ERP-Channel-Operations#example-of-computing-global-field-power</a></span></span></span></li><li><span style="color:rgb(0,0,0)">You can find out more about GFP and
how to compute GFP by reviewing articles/tools developed by Lehman,
Faber, Britz, Michel, Koenig, and others, (e.g., CARTOOL or microstates
toolboxes in matlab/eeglab<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">, see also brainstorm</span>), all easy to find via Google and/or Google Scholar.</span></li><li><span style="color:rgb(0,0,0)">Regarding graphics it is possible to get something like the graphics in the article you mentioned<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small"> with matlab and/or eeglab</span>, but you would need to compute GFP first (there is a microstate toolbox for eeglab <span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">you can look into</span>)</span></li><li><span style="color:rgb(0,0,0)">If
you want to replicate exactly the analysis in the article you mentioned, consider
contacting that team, they may be able to share their exact method<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">s/scripts</span> with you.</span></li><li><span style="color:rgb(0,0,0)"><span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">Fyi, g</span>reat books for EEG beginners are Mike X Cohen's books, and Luck's two handbooks, both of which I consider core reading.<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small"> </span>Both Cohen and Luck have extensive materials online that one can review.<span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">
Also as a new user to eeglab, please check out if you haven't had a
chance to the extensive eeglab wiki and eeglab school videos.</span></span></li><li><span style="color:rgb(0,0,0)"><span class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small">Caveat:
Note that 2-minutes is a somewhat short period of time per participant,
but it should be usable, and many groups publish on similar brief data.</span></span></li></ul></div><div class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small;color:rgb(0,0,255)"><br></div><div class="gmail_default" style="font-family:arial,helvetica,sans-serif;font-size:small;color:rgb(0,0,255)"><br></div></div></div></div></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Fri, Jan 25, 2019 at 1:13 PM Alex Scodellaro <<a href="mailto:ajscod@gmail.com">ajscod@gmail.com</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 style="font-family:verdana,sans-serif"><div dir="ltr" style="color:rgb(0,0,0);font-family:Arial,Helvetica,sans-serif"><div style="font-family:verdana,sans-serif">Dear all,</div><div style="font-family:verdana,sans-serif"><br></div><div style="font-family:verdana,sans-serif">I am a junior neuromarketing researcher and am new to the EEGLAB program. I have 14 EEG recordings of 2-minute participant exposure to advertisement. I have segmented each data-set into 'epochs of interest'.</div><div style="font-family:verdana,sans-serif"><br></div></div><blockquote style="color:rgb(0,0,0);font-family:Arial,Helvetica,sans-serif;margin:0px 0px 0px 40px;border:medium none;padding:0px"><div dir="ltr"><div style="font-family:verdana,sans-serif">I wish to ask how I can determine the total <i>average</i> GFP theta z-score and GFP alpha z-scores similar to the paper below. And further, can EEGLAB produce graphs as shown in the paper?</div><div style="font-family:verdana,sans-serif"><br></div></div></blockquote><blockquote style="color:rgb(0,0,0);font-family:Arial,Helvetica,sans-serif;margin:0px 0px 0px 40px;border:medium none;padding:0px"><div dir="ltr"><div style="font-family:verdana,sans-serif">Also, how different are GFP and FFT analyses? From what I can understand, they yield similar results.</div></div></blockquote><div dir="ltr" style="color:rgb(0,0,0);font-family:Arial,Helvetica,sans-serif"><div style="font-family:verdana,sans-serif"><br></div><div style="font-family:verdana,sans-serif"><i>Gordon, Ross et. al (2017). Using EEG to Examine the Role of Attention, Working Memory, Emotion, and Imagination in Narrative Transportation. </i><br></div><div style="font-family:verdana,sans-serif"><br></div><div style="font-family:verdana,sans-serif"><br></div><div style="font-family:verdana,sans-serif"><br></div><div style="font-family:verdana,sans-serif">I would really appreciate any and all help!</div><div style="font-family:verdana,sans-serif"><br></div><div style="font-family:verdana,sans-serif">Thank you in advance.</div><div style="font-family:verdana,sans-serif">Alex</div></div></div><div><div dir="ltr" class="gmail-m_-5114227973860943679gmail_signature"><div dir="ltr"><div><div dir="ltr"><table style="width:337.5pt;border-collapse:collapse" width="450" cellspacing="0" cellpadding="0" border="0">
<tbody><tr>
<td style="width:297pt;padding:0cm" width="396" nowrap>
<p style="margin-bottom:7.5pt;line-height:12pt"><b><span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:rgb(33,33,33)">Alexander Scodellaro</span></b><span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:rgb(33,33,33)"> <br>
<a href="mailto:ajscod@gmail.com" target="_blank"><span style="color:rgb(71,124,204)">ajscod@gmail.com</span></a> / 0422211619</span></p>
</td>
</tr>
<tr>
<td style="padding:0cm"></td>
</tr>
<tr>
<td style="padding:0cm"></td>
</tr>
<tr>
<td style="padding:0cm">
<p style="line-height:15pt"><span style="font-size:7.5pt;font-family:"Times New Roman",serif;color:black" lang="EN-US">This email (and any attachments) is confidential and may be subject to legal or other professional privileges. It is intended solely for the receipt of the named addressee(s). It is subject to copyright and may only be copied or distributed with the consent of the copyright owner. If you are not a named addressee, you must not use, disclose, retain or reproduce all or any part of the information contained in this email or any attachments. Please notify the sender immediately by return email and destroy all copies of the email. Any confidentiality, privilege or copyright is not waived or lost because this email has been sent to you by mistake.</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:black"></span></p>
</td>
</tr>
</tbody></table></div></div></div></div></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></div>