<div dir="ltr">Dear Andria and Arno,<div><br></div><div>Yes Arno is right. I confused FFT with Wavelet Transform.</div><div>My previous comment,</div><div><blockquote type="cite" style="color:rgb(80,0,80)"><div dir="ltr"><p class="MsoNormal">> In your case though, you want to compare whether using the whole epoch baseline makes the data look more reasonable or not. If you do this, then you are evaluating the deviation from the mean across all recording time.</p></div></blockquote></div><div class="gmail_extra">applies to the case of power calculated by Wavelet Transform.</div><div class="gmail_extra"><br></div><div class="gmail_extra">> Baseline is only subtracted (in log or linear space) when performing time-frequency decompositions (newtimef function).<br></div><div class="gmail_extra"><br></div><div class="gmail_extra">This is equivalent to dividing all datapoints by pre-stimulus mean, so this is normalization.<br></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 Thu, Jan 26, 2017 at 2:50 PM, Arnaud Delorme <span dir="ltr"><<a href="mailto:arno@ucsd.edu" target="_blank">arno@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 style="word-wrap:break-word">There is no baseline “normalization” when computing the data or ICA component spectrum using spectopo. Baseline is only subtracted (in log or linear space) when performing time-frequency decompositions (newtimef function).<div><br></div><div>Arno</div><div><div class="gmail-h5"><div><br><div><blockquote type="cite"><div>On Jan 26, 2017, at 2:43 PM, Makoto Miyakoshi <<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>> wrote:</div><br class="gmail-m_843240632946716781Apple-interchange-newline"><div><div dir="ltr">Dear Andria,<div><br></div><div><p class="MsoNormal">> 1- In the case of mine, where there is no markers, and then no baseline normalization, do you think produces power specturm with dB (produced by spectopo) can lead to problems is correct? or using microvolts squared (uV2) should correct? or both dB and microvolts squared are acceptable?</p><p class="MsoNormal"><br></p><p class="MsoNormal">All are correct. That being said, the problem of using uV^2 is that the value tend to be ridiculously large. Convert to dB makes the data more intuitively understandable. Therefore I personally prefer to converting to dB. In your case though, you want to compare whether using the whole epoch baseline makes the data look more reasonable or not. If you do this, then you are evaluating the deviation from the mean across all recording time.</p><p class="MsoNormal"><br></p><p class="MsoNormal">> 2- Does "spectopo" function apply baseline normalization by default from EEGLAB GUI?</p></div><div class="gmail_extra"><br></div><div class="gmail_extra">Yes. To turn it off, you need to use an optional input.</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 Thu, Jan 26, 2017 at 1:19 AM, Andria Lan <span dir="ltr"><<a href="mailto:andrialan108@gmail.com" target="_blank">andrialan108@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 dir="ltr">Dear Makoto, <div><br></div><div>I have an issue that is related to our previous discussion. </div><div><br></div><div>As you know that my data don't have any markers, hence, my analysis will focuses mainly on ERSPs. I'll display the following points and then ask my questions.</div><div><br></div><div>In one of the EEGLAB discussions, <b>according to Arno: </b><span style="font-family:calibri,sans-serif;font-size:11pt"><b>spectrum returned in EEGLAB is in unit dB</b> which is <b>10*log10(uV^2/Hz)</b>. Everything is good till now. In addition, according to some references:</span><br></div><div><span style="font-family:calibri,sans-serif;font-size:11pt"><br></span></div><div><p class="MsoNormal"><b>dB<i><sub>tf </sub></i>= 10*log<i><sub>tf</sub></i>*(activity<i><sub>tf</sub></i><sub> / </sub>baseline<i><sub>f</sub></i>)</b>. </p><p class="MsoNormal"><br></p><p class="MsoNormal">Now, please focus at this point:</p><p class="MsoNormal">In this last dB formula, you can see that the existence of both <b>dB</b> and<b> baseline (baseline normalization)</b>. This means that, existence of dB is required the existence of baseline normalization. Beside, baseline normalization can be implemented in the case of having markers in order to place the baseline before the stimulus onset. In sum, with dB and baseline normalization are located with dataset that have markers where power spectrum unit in this case is dB (that is mentioned by Arno up) which I believe produced by spectopo. </p><p class="MsoNormal"><br></p><p class="MsoNormal"><br></p><p class="MsoNormal">Consequently, my two questions:</p><p class="MsoNormal"><br></p><p class="MsoNormal">1- In the case of mine, where there is no markers, and then no baseline normalization, do you think produces power specturm with dB (produced by spectopo) can lead to problems is correct? or using microvolts squared (uV2) should correct? or both dB and microvolts squared are acceptable?</p><p class="MsoNormal"><br></p><p class="MsoNormal">2- Does "spectopo" function apply baseline normalization by default from EEGLAB GUI?</p><p class="MsoNormal"><br></p><p class="MsoNormal">Thanks for your aptionance and assistance. </p><span class="gmail-m_843240632946716781gmail-HOEnZb"><font color="#888888"><p class="MsoNormal"><br></p><p class="MsoNormal">Andria</p></font></span></div><span style="font-size:11pt;line-height:115%;font-family:calibri,sans-serif"> <br></span></div><div class="gmail-m_843240632946716781gmail-HOEnZb"><div class="gmail-m_843240632946716781gmail-h5"><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Jan 26, 2017 at 12:54 AM, Andria Lan <span dir="ltr"><<a href="mailto:andrialan108@gmail.com" target="_blank">andrialan108@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 dir="ltr">Dear Makoto, <div><br></div><div>Thanks a ton. Without you and your help, I really don't know what to do.</div><div><br></div><div>Wish you all the best and the success as well. </div><span class="gmail-m_843240632946716781gmail-m_2023968113274710459HOEnZb"><font color="#888888"><div><br></div><div>Andria</div></font></span></div><div class="gmail-m_843240632946716781gmail-m_2023968113274710459HOEnZb"><div class="gmail-m_843240632946716781gmail-m_2023968113274710459h5"><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Jan 25, 2017 at 3:04 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: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 Andria,<div><br></div><div>If you don't have event markers, you cannot apply event-related potential analysis. All you can use is basically spectra in EEGLAB STUDY.</div><div><br></div><div><span><div>> 1- For first subject, how did you recommend saving the recorded data (during the experiment) to be used later at preprocessing stage and STUDY option?</div><div><br></div></span><div>Save as a single .set file. Again, if you don't have events, that's the only option for you.</div><span><div><br></div><div>> 2- However, do you recommend <b>ALWAYS</b> using *<b>only</b>* one file to save the data for each subject (all conditions) with both ERP and ERSP analysis?</div></span></div><div class="gmail_extra"><br></div><div class="gmail_extra">Yes, I recommend that. Historically, EEGLAB supported separate .set files for different conditions, but now STUDY.design can handle them, and the old method tend to have compatibility problem so less stable.</div><span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370HOEnZb"><font color="#888888"><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div></font></span><div><div class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370h5"><div class="gmail_extra"><br></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Jan 17, 2017 at 6:12 PM, Andria Lan <span dir="ltr"><<a href="mailto:andrialan108@gmail.com" target="_blank">andrialan108@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 dir="ltr"><div>Dear Makoto,</div><div><br></div><div>Thanks a lot for your prompt reply and the useful link. However, I don't have any events (markers) for participants' recorded data. I have only the signal resulting from the task. </div><span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-"><div><br></div><div>Here is the scenario:</div><div><br></div><div>For the sake of clarity (for now), I have:</div><div><br></div><div>a) 30 subjects </div><div>b) 2 conditions.</div><div>c) 10 visual task trials for each condition.</div><div>d) subjects only need to see the trials.</div></span><div>e) not button pressing-->no ERP analysis (analysis only based "time-frequency" or "ERSP")</div><span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-"><div><br></div><div>My questions:</div><div><br></div><div>1- For first subject, how did you recommend saving the recorded data (during the experiment) to be used later at preprocessing stage and STUDY option?</div><div><br></div><div>2- However, do you recommend <b>ALWAYS</b> using *<b>only</b>* one file to save the data for each subject (all conditions) with both ERP and ERSP analysis?</div><div><br></div><div><br></div></span><div><br><div class="gmail_chip gmail_drive_chip" style="width:396px;height:18px;max-height:18px;padding:5px;color:rgb(34,34,34);font-family:arial;font-style:normal;font-weight:bold;font-size:13px;border:1px solid rgb(221,221,221);line-height:1;background-color:rgb(245,245,245)"><a href="https://drive.google.com/file/d/0B430Bz2U6pH-N0J1TnJITk5rblk/view?usp=drive_web" style="display:inline-block;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;text-decoration:none;padding:1px 0px;border:none;width:100%" target="_blank"><img style="vertical-align: bottom; border: none; border-image-source: initial; border-image-slice: initial; border-image-width: initial; border-image-outset: initial; border-image-repeat: initial;" src="https://ssl.gstatic.com/docs/doclist/images/icon_11_image_list.png"> <span dir="ltr" style="color:rgb(17,85,204);text-decoration:none;vertical-align:bottom">STUDY for loading the data.png</span></a></div><br></div><div>Thank you.</div><span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-HOEnZb"><font color="#888888"><div>Andria</div></font></span></div><div class="gmail_extra"><br><div class="gmail_quote"><span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-">On Fri, Jan 13, 2017 at 3:30 PM, Makoto Miyakoshi <span dir="ltr"><<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>></span> wrote:<br></span><div><div class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-h5"><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 Andria,<div><br></div><div>If you follow our recommended preprocessing steps, you don't need to average any data before STUDY does it on it own.</div><span><div><br></div>> is it enough (and correct way) loading the data files (for each subject) one-by-one under each condition using the “STUDY” option of EEGLAB?<div><br></div></span><div>Do not separate .set into conditions. See this section.</div><div><a href="https://sccn.ucsd.edu/wiki/Makoto%27s_preprocessing_pipeline#Create_STUDY_.2801.2F05.2F2017_updated.29" target="_blank">https://sccn.ucsd.edu/wiki/Mak<wbr>oto%27s_preprocessing_pipeline<wbr>#Create_STUDY_.2801.2F05.2F201<wbr>7_updated.29</a></div><div><br></div><div>Makoto</div><div><br></div><div><br></div><div><div class="gmail_extra"><br><div class="gmail_quote"><div><div class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-m_4927647895087551034h5">On Thu, Jan 12, 2017 at 1:58 AM, Andria Lan <span dir="ltr"><<a href="mailto:andrialan108@gmail.com" target="_blank">andrialan108@gmail.com</a>></span> wrote:<br></div></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-style:solid;border-left-color:rgb(204,204,204);padding-left:1ex"><div><div class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-m_4927647895087551034h5"><div dir="ltr"><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">Dear EEGLAB list, <span></span></span></p><div style="margin-bottom:0.0001pt;line-height:normal"><span style="font-size:12pt;font-family:arial,sans-serif"><span> </span></span><br class="gmail-m_843240632946716781webkit-block-placeholder"></div><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">I need your advice about implementing this scenario using EEGLAB toolbox.<span></span></span></p><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">I have this issue and I need your advice:</span><span style="font-size:9.5pt;font-family:arial,sans-serif"><span></span></span></p><div style="margin-bottom:0.0001pt;line-height:normal"><span style="font-size:12pt;font-family:arial,sans-serif"> </span><span style="font-size:9.5pt;font-family:arial,sans-serif"><span></span></span><br class="gmail-m_843240632946716781webkit-block-placeholder"></div><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">I performed my experiment on several subjects, the task doesn't required
any events because it's only about watching several trials where each belongs
to one specific condition. Hence, I ended up with several data files for each
subject. In addition, I don’t have any epochs in those files, and my aim is performing
time-frequency analysis. Now, in order to do such analysis using EEGLAB
toolbox, is it enough (and correct way) loading the data files (for each
subject) one-by-one under each condition using the “STUDY” option of EEGLAB?<span></span></span></p><div style="margin-bottom:0.0001pt;line-height:normal"><span style="font-size:12pt;font-family:arial,sans-serif"><span> </span></span><br class="gmail-m_843240632946716781webkit-block-placeholder"></div><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">Do average the results (files) for each subject is required at this
stage, or by using the STUDY option this method will be accomplished automatically?<span></span></span></p><div style="margin-bottom:0.0001pt;line-height:normal"><span style="font-size:12pt;font-family:arial,sans-serif"><span> </span></span><br class="gmail-m_843240632946716781webkit-block-placeholder"></div><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">Any help would be highly appreciated. <span></span></span></p><div style="margin-bottom:0.0001pt;line-height:normal"><span style="font-size:12pt;font-family:arial,sans-serif"><span> </span></span><br class="gmail-m_843240632946716781webkit-block-placeholder"></div><p class="MsoNormal" style="margin-bottom:0.0001pt;line-height:normal;background-image:initial;background-size:initial;background-origin:initial;background-clip:initial;background-position:initial;background-repeat:initial"><span style="font-size:12pt;font-family:arial,sans-serif">Thanks.<span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-m_4927647895087551034m_5712999676294655333gmail-HOEnZb"><font color="#888888"><span></span></font></span></span></p><span class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail-m_4927647895087551034m_5712999676294655333gmail-HOEnZb"><font color="#888888"><div style="margin-bottom:0.0001pt;line-height:normal"><span style="font-size:12pt;font-family:arial,sans-serif"><span> </span></span><br class="gmail-m_843240632946716781webkit-block-placeholder"></div>
<span style="font-size:12pt;line-height:107%;font-family:arial,sans-serif">Andria </span><br></font></span></div>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail-m_843240632946716781gmail-m_2023968113274710459m_-3364356658216027370m_5324952658447431368gmail_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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</div></div></blockquote></div><br><br clear="all"><div><br></div>-- <br><div class="gmail-m_843240632946716781gmail_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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______________________________<wbr>_________________<br>Eeglablist page: <a href="http://sccn.ucsd.edu/eeglab/eeglabmail.html" target="_blank">http://sccn.ucsd.edu/eeglab/<wbr>eeglabmail.html</a><br>To unsubscribe, send an empty email to <a href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu" target="_blank">eeglablist-unsubscribe@sccn.<wbr>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.<wbr>edu</a></div></blockquote></div><br></div></div></div></div></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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