<div dir="ltr">Thanks you Johanna!<div><br><div>John, there is related discussion going on on the list, which is about the similar case of using wavelet.</div><div><br></div><div>Makoto</div><div><br></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Aug 9, 2016 at 1:32 PM, Johanna Wagner <span dir="ltr"><<a href="mailto:joa.wagn@gmail.com" target="_blank">joa.wagn@gmail.com</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 John, dear Makoto,<div><br></div><div>the FFT output from newtimef() is normalized by window length. timefreq() is a function within newtimef() - newtimef() is scaling the timefreq() output.</div><div>You can get all timefreq() output values via newtimef(), so I would recommend using the latter.<br></div><div><br></div><div>John, newtimef() is dividing by the baseline (by default that is the period before 0 in an epoch - if not specified otherwise) - as Makoto wrote.</div><div>Thus the power values are normalized relative to baseline and no scaling is needed...</div><div><br></div><div>You do not need to use rmbase() as it removes the baseline in the timedomain - newtimef() is removing average power at each frequency instead.</div><div> </div><div>Best, johanna </div><div><br></div><div><br></div><div><br></div><div class="gmail_extra"><div><div class="h5"><br><div class="gmail_quote">2016-08-09 11:25 GMT-07:00 Makoto Miyakoshi <span dir="ltr"><<a href="mailto:mmiyakoshi@ucsd.edu" target="_blank">mmiyakoshi@ucsd.edu</a>></span>:<br><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 dir="ltr">Dear John,<span><div><br></div>> I think it is percent of baseline?<div><br></div></span><div>No. If I remember correctly, it is dB change relative to the baseline value. It's usually negative latency, but if data are continuous (which may be your case), it should be whole-epoch value.</div><span><div><br></div><div>> What I would really like to have is just µV^2 so I can eventually compare, say, C3 between conditions and see the difference. Is that possible?</div><div><br></div></span><div>We just confirmed today that output from timefreq() is NOT normalized by length of data. Which means that if your wavelet window size is longer, it returns larger values. I'm not sure if this is corrected in newtimef() which calls timefreq() but I guess it is so anyways. We started working on this issue, so you'd better wait for our update. Otherwise, if you don't mind coding yourself, you can normalize the 'tf' output from timefreq() by the length of wavelet which you can obtain by using dftfilt3().</div><div><br></div><div>Makoto</div><div><br></div><div><br><div class="gmail_extra"><br><div class="gmail_quote"><div><div>On Sat, Aug 6, 2016 at 10:56 AM, John Johnson <span dir="ltr"><<a href="mailto:john@johnjohnson.info" target="_blank">john@johnjohnson.info</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><div dir="ltr">I've combed the interwebs and still haven't found a good answer.<div><br></div><div>My data has a -5s rest period followed by a 20s active period (task related experiment, not event related). My pipeline includes rmbase(), among other things.</div><div>Now, when I run newtimef, I can create nice plots from the ersp obtained using:</div><div><br></div><div><p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> [ersp, itc, powbase, times, freqs, erspboot, itcboot, tfdata] = <span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> newtimef( EEG.data(channel,:,:),<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> EEG.pnts, [EEG.xmin EEG.xmax]*1000,<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> EEG.srate,<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> cycles,<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> <span style="color:rgb(178,69,243)">'plotersp'</span>, <span style="color:rgb(178,69,243)">'off'</span>,<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> <span style="color:rgb(178,69,243)">'plotitc'</span>, <span style="color:rgb(178,69,243)">'off'</span>,<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> <span style="color:rgb(178,69,243)">'freqs'</span>, [2 25],<span style="color:rgb(4,51,255)">...</span></p>
<p style="margin:0px;font-size:10px;line-height:normal;font-family:Courier"> <span style="color:rgb(178,69,243)">'scale'</span>, <span style="color:rgb(178,69,243)">'abs'</span>);</p>
<p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><br></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px">I just do a mean(ersp, 2) to average across time, then mean() across subjects. The x-axis of my plot is frequency, but I don't know what the units for the y-axis would be. I think it is percent of baseline? Now if the values I'm seeing are percent of baseline, that means they're measured relative to the baseline, which is redundant because I've already removed the baseline.</p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px">If I add the <span style="font-size:10px;color:rgb(178,69,243)">'baseline'</span><span style="font-size:10px">,[NaN] argument to newtimef, my plots then look like ski slopes (high at low frequencies, low at higher frequencies).</span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px">What I would really like to have is just µV^2 so I can eventually compare, say, C3 between conditions and see the difference. Is that possible?</span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px"><br></span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px">I've seen this question several times on the 'net, but haven't found a good answer.</span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px"><br></span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px">Thanks,</span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px">John</span></p><span><font color="#888888"><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px"><br></span></p><p style="margin:0px;font-size:12px;line-height:normal;font-family:Courier;min-height:14px"><span style="font-size:10px"><br></span></p><div><br></div>-- <br><div data-smartmail="gmail_signature">Sent from a MacBook Pro<br></div>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div 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>
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