<div dir="ltr">Hi Vitoria,<div><br></div><div style>I have only one thing to add to Ingrid's clear explanation. For frequency analysis, it's mostly a matter of noise. If you do not demean, the 0Hz been can bleed into all other frequency bins in a funny but patterned way. For detrending, the same story applies. When not detrending, the power of the center frequency of the linear trend (this frequency is very low), can bleed into other bins. </div>
<div style><br></div><div style>The FAQs have two great example on this:</div><div style><a href="http://fieldtrip.fcdonders.nl/faq/why_does_my_tfr_look_strange">http://fieldtrip.fcdonders.nl/faq/why_does_my_tfr_look_strange</a><br>
</div><div style><a href="http://fieldtrip.fcdonders.nl/faq/why_does_my_tfr_look_strange_part_ii">http://fieldtrip.fcdonders.nl/faq/why_does_my_tfr_look_strange_part_ii</a><br></div><div style><br></div><div style>Both are specific for when using 'mtmconvol' as frequency method (why this is so is explained shortly in the first FAQ), although in principle the issues could also occur using the other methods.<br>
</div><div style><br></div><div style>Hope it helps!</div><div style><br></div><div style>All the best,</div><div style>Roemer</div><div style><br></div><div style><br></div><div class="gmail_extra"><br><div class="gmail_quote">
On Sun, Jan 6, 2013 at 3:24 AM, Ingrid Nieuwenhuis <span dir="ltr"><<a href="mailto:inieuwenhuis@berkeley.edu" target="_blank">inieuwenhuis@berkeley.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">
Hi Vitoria,<br>
<br>
The problem with these things is, it depends on what your interested in (hypothesis) and which methods you're using to analyze the data (ERP or frequanalysis, with our without ICA). All analysis steps have different pro and cons, so depending on your hypotheses and effects, what's good in one setup can be bad in the next. So you have to think of what the measures do, and how that effects your data.<br>
<br>
But now for some answers :) I'm just using a lot of experience and some common sense, maybe people can add in some refs and math if they know :)<br>
Demeaning just subtracts the mean of the specified time window (or indeed whole trial) from all samples<br>
detrending removes linear trend (you can also remove higher order trends, just for completeness)<br>
<br>
For ERPs you generally do want to demean using the baseline window, so the effect cancels out pre-stim. You don't want to detrend here, since often the ERP can have late components, and the signal might not be back to baseline yet. If you detrend in such a case, you will decrease the value samples late in the trials and increase the values during baseline. You will tilt the data (end down thus start up). But if you expect a linear trend due to equipment drift over longer time, that can muddle the ERP effect, then you might want to detrend. Also when the signal is noisy (high amplitude noise) at the end (due to speach artifacts), detrending might be dangerous.<br>
<br>
For frequency analysis, demeaning has (as far as I know) no effect, since subtracting a constant does not change the frequency info in the signal. I know people do tend to detrend before freq analysis (so I also tend to do that), but I have to admit, I don't know why really. Maybe to get rid of the drift, so it does not end up in the low frequencies. But again, the effect of detrending (which freqs it affects) depends how long your time window is, and which frequencies your interested in. If you are interested in really low frequencies, detrending might change your effects.<br>
<br>
Hope this helps somewhat,<br>
Ingrid<div class=""><div class="h5"><br>
<br>
<br>
On 1/5/2013 2:21 AM, Vitória Magalhães Piai 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">
Dear ftrippers,<br>
<br>
I'm having a discussion with a colleague on something that is still a bit unclear to us. Since I trust the knowledge going around here a lot, I thought it would be my best chance to get a good answer: When should we demean/detrend?<br>
<br>
As relevant background, our EEG datasets involve speech production on every trial.<br>
We read in the data, use ft_databrowser to mark the artefacts and then do complete artefact rejection with ft_rejectartifact. The trials often include speech (onset).<br>
I see in the tutorial that the cfg for preprocessing is pretty simple, and ft_preprocessing default has no detrend/demean.<br>
But in the FT example 'Reading and pre-processing EEG data', the cfg is<br>
<br>
cfg.demean = 'yes';<br>
cfg.baselinewindow = [-0.2 0];<br>
<br>
<br>
In my data, I used cfg.demean = 'yes'; with no cfg for the baseline window because I don't want to correct the signal with a specific interval (and I assume this will take the whole segment then).<br>
Our concern is that, given that people speak during part of the trial (always towards the end), using demean here is not a good idea (the signal changes induced by moving the jaws, etc., are included in the calculation). Is this necessarily the case or can it be fixed with subsequent computations (see below)? Do I need to go through artefact rejection again? My guess would be that the damage caused by having demean here doesn't change that much where the eyeblinks are and I always take quite broad windows to mark the artefacts, so at least for the AR I should be safe, but I'd like to check that with you guys.<br>
<br>
Then, when calculating ERPs, I had both demean and detrend before timelocking.<br>
But for the TFRs, I didn't do any of these (dunno why). I'm using the ft_freqanalysis after the 2011 change (removing the first order linear trend from the time domain data).<br>
Do I need to redo my TFRs or is it enough if I do sanity checks and everything is in place (like visual alpha and gamma, etc.)?<br>
<br>
And my last question, for once and for all, so that I get it right next time from the start (assuming that I'll always have EEG speech production data with ERPs and TFRs analysed). Is this the best way to do it?<br>
- preprocess with default (so NO detrend and NO demean)<br>
- then demean and detrend for ft_timelockanalysis and ft_freqanalysis<br>
<br>
Thanx a lot, and (keeping to the Dutch tradition) all the best for 2013!<br>
Vitoria<br>
<br>
<br>
<br>
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</blockquote>
<br></div></div><span class=""><font color="#888888">
-- <br>
Ingrid Nieuwenhuis PhD<br>
Postdoctoral Fellow<br>
Sleep and Neuroimaging Laboratory<br>
Department of Psychology<br>
University of California, Berkeley<br>
California 94720-1650<br>
Tolman Hall, room 5305</font></span><div class=""><div class="h5"><br>
<br>
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</div></div></blockquote></div><br></div><br clear="all"><div><br></div>-- <br><font size="3"><font color="darkblue"><font face="calibri">Roemer
van der Meij M.Sc.<br>
PhD Candidate<br>
Donders Institute for Brain, Cognition and Behaviour<br>
Centre for Cognition<br>
P.O. Box 9104<br>
6500 HE Nijmegen<br>
The Netherlands<br>
Tel: +31(0)24 3655932<br>
E-mail: <a href="mailto:r.vandermeij@donders.ru.nl" target="_blank">r.vandermeij@donders.ru.nl</a></font></font></font><div style="padding:0px;margin-left:0px;margin-top:0px;overflow:hidden;word-wrap:break-word;color:black;font-size:10px;text-align:left;line-height:130%">
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