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Thanks JM, all clear now. FAQ updated: Done!<br>
Cheers,<br>
Ingrid<br>
<br>
<div class="moz-cite-prefix">On 1/7/2013 12:07 PM, jan-mathijs
schoffelen wrote:<br>
</div>
<blockquote
cite="mid:CD054D4F-582A-4CA8-850C-8E65BAC51FD1@donders.ru.nl"
type="cite">
<div>Dear Ingrid and others,</div>
<div><br>
</div>
<div>I forgot to mention, the default has changed one year ago,
according to the following thread on the list:</div>
<div><br>
</div>
<a moz-do-not-send="true"
href="http://mailman.science.ru.nl/pipermail/fieldtrip/2012-January/004666.html">http://mailman.science.ru.nl/pipermail/fieldtrip/2012-January/004666.html</a>
<div><br>
</div>
<div>Apologies for not having updated the FAQ. Ingrid, would you
mind giving this a shot?</div>
<div><br>
</div>
<div>Best,</div>
<div><br>
</div>
<div>Jan-Mathijs</div>
<div><br>
</div>
<div><br>
</div>
<div><br>
<div>
<div>On Jan 7, 2013, at 8:31 PM, Ingrid Nieuwenhuis wrote:</div>
<br class="Apple-interchange-newline">
<blockquote type="cite">
<meta content="text/html; charset=ISO-8859-1"
http-equiv="Content-Type">
<div text="#000000" bgcolor="#FFFFFF"> Hi Roemer,<br>
<br>
Thanks for pointing to these questions. I'm a little bit
confused about the default behavior with cfg.polyremoval
as described there. So it seems the default of polyremoval
for ft_freqanalysis is 1, meaning detrending always
happens unless you specify otherwise, correct? So that
means you don't have to call preprocessing with
cfg.detrend = 'yes', correct? But you do have to specify
cfg.demean = 'yes' in preprocessing? Or does removing the
linear trend (which is the default) in ft_freqanalysis
automatically also demean the data? From the text under
the figure in <a moz-do-not-send="true"
class="moz-txt-link-freetext"
href="http://fieldtrip.fcdonders.nl/faq/why_does_my_tfr_look_strange">http://fieldtrip.fcdonders.nl/faq/why_does_my_tfr_look_strange</a>
it almost looks that way. Because it talks about
cfg.polyremoval in the context of demeaning, not
detrending. I don't find that text very clear by the way.
Also, the title above the figure says "TFR before (left)
and after (right) subtracting the DC component in the time
domain", while when I look at the code it seems it should
be "TFR of channel with large DC component (left) and
channel without DC component (right) after ft_freqanalysis
without demeaning". I'd be happy to update the FAQ, but
first wanted to check whether I understand correctly :)<br>
<br>
Cheers,<br>
Ingrid<br>
<br>
<br>
<div class="moz-cite-prefix">On 1/7/2013 4:28 AM, Roemer
van der Meij wrote:<br>
</div>
<blockquote
cite="mid:CA+WpQ37gyb0Twxk3m6-m+9K1qbPDXudSXxKcuYnRtimQ9-Uqjg@mail.gmail.com"
type="cite">
<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 moz-do-not-send="true"
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 moz-do-not-send="true"
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
moz-do-not-send="true"
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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</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 moz-do-not-send="true"
href="mailto:r.vandermeij@donders.ru.nl"
target="_blank">r.vandermeij@donders.ru.nl</a></font></font></font>
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</blockquote>
<br>
<pre class="moz-signature" cols="72">--
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305</pre>
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class="Apple-style-span" style="border-collapse:
separate; color: rgb(0, 0, 0); font-family:
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">
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-webkit-nbsp-mode: space; -webkit-line-break:
after-white-space; "><span
class="Apple-style-span"
style="border-collapse: separate; color:
rgb(0, 0, 0); font-family: Helvetica;
font-size: medium; font-style: normal;
font-variant: normal; font-weight: normal;
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word-spacing: 0px;
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-webkit-text-stroke-width: 0px; ">
<div style="word-wrap: break-word;
-webkit-nbsp-mode: space;
-webkit-line-break: after-white-space; ">
<div>Jan-Mathijs Schoffelen, MD PhD </div>
<div><br>
</div>
<div>Donders Institute for Brain, Cognition
and Behaviour, <br>
Centre for Cognitive Neuroimaging,<br>
Radboud University Nijmegen, The
Netherlands</div>
<div><br>
</div>
<div>Max Planck Institute for
Psycholinguistics,</div>
<div>Nijmegen, The Netherlands</div>
<div><br>
</div>
<div><a class="moz-txt-link-abbreviated" href="mailto:J.Schoffelen@donders.ru.nl">J.Schoffelen@donders.ru.nl</a></div>
<div>Telephone: +31-24-3614793</div>
</div>
</span></div>
</span></div>
</span></div>
</span></div>
</div>
<br>
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</blockquote>
<br>
<pre class="moz-signature" cols="72">--
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305</pre>
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