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There is an article by Truccolo et al in Clinical Neurophysiology
(Trial-to-trial variability of cortical evoked responses: implications
for the analysis of functional connectivity) which examines such a
subtraction of the evoked response. I believe the idea is that your
averaged ERP does not exactly represent all potential evoked activity
in a given trial. Therefore some residual evoked activity will survive
a "single trial minus ERP" routine. ERSP data contains both evoked and
induced power, which are tough to separate without making some
assumptions about the data. I don't think that you can subtract the
ERP from every single trial, subject it to TF analysis, and say that
the resulting ERSP map shows phase varying (or induced) responses <i>only</i>.
To do that, you would have to assume that the ERP subtraction accounted
for exactly all of the evoked power activity in every single trial.<br>
<br>
I was interested in your last comment Stan - do you have any references
about saccades and gamma?<br>
<br>
thanks,<br>
Brian<br>
<br>
<br>
Stanley Klein wrote:
<blockquote
cite="mid:9016c9f10804151341y33cefd70w3664e9331a21ae5a@mail.gmail.com"
type="cite">It looks like there is some consensus on whether to
subtract first and then the TF or vice versa. That's nice. [On the
other hand subtracting first is a nice way to get rid of ERP, but there
are better ways, as described next.]<br>
<br>
Andrei, I'm not sure I understood your last comment or question, but I
have a related question. Whenever one does time-frequency power plots I
would think that one should ALWAYS first get the time locked average
and subtract it off of all the individual trials. Then one could do a
TF plot of each. How many on this list do that? I suspect that people
mix together the standard evoked response and also the phase varying
response. Why do that since its so easy to show the the two TF plots
separately.<br>
<br>
Also I've heard rumors that saccades and microsaccades are responsible
for most EEG gamma oscillations. So one should also put those events
into a separate category too. Too bad things are complicated. But it
makes life interesting. <br>
Stan<br>
<br>
<div class="gmail_quote">On Tue, Apr 15, 2008 at 9:38 AM, Andrei
Medvedev <<a moz-do-not-send="true"
href="mailto:am236@georgetown.edu">am236@georgetown.edu</a>> wrote:<br>
<blockquote class="gmail_quote"
style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">Hi
All,<br>
<br>
I think this was just a small mistake confusing options 1 and 2. I
believe so because it is option 1 (not 2) which would require pairing
of trials to do EEG subtraction first, which is indeed a rare
possibility.<br>
<br>
To me, it also looks like option 2 is more correct because TF analysis
(in its most common 'spectral perturbation' or 'induced activity'
version) looks for changes in spectra regardless of phase. This is why
if you analyze only one condition, you do TF first and then average
trials. Similar thing should then be done when comparing two
conditions, that is, TF first.<br>
<br>
With one condition, you can also do averaging first and then TF, in
this case you would have the so-called 'evoked' responses in the
frequency domain (instead of 'induced' responses mentioned above).
Evoked activity shows you the frequency components phase-locked to the
stimulus (a more strict form of time locking). If you try to do similar
thing with two conditions (trials should be paired somehow but there is
no 'natural' way to pair them, only in some special circumstances), you
will have a problem of phase relations between conditions and may get
different answers (such as sum/subtraction of in-phase/out-of-phase
sine waves, as other people point out). This would be a very different
response and I believe nobody is doing this. But theoretically, this
type of response can be explored as well (if you have a 'natural' way
of pairing trials).<br>
<br>
BTW, I haven't tried to use TF decomposition in EEGLAB applied to the
averaged ERP (i.e., averaging of trials first, then TF resulting in an
'evoked' response for one condition). Has anyone tried this?<br>
<br>
Regards,<br>
Andrei.<br>
<br>
Georgetown University<br>
<div>
<div class="Wj3C7c"><br>
<br>
----- Original Message -----<br>
From: Arnaud Delorme <<a moz-do-not-send="true"
href="mailto:arno@cerco.ups-tlse.fr">arno@cerco.ups-tlse.fr</a>><br>
Date: Sunday, April 13, 2008 1:53 pm<br>
Subject: Re: [Eeglablist] Time-frequency analysis (subtraction first or
analysis first)<br>
<br>
> Dear Hsu,<br>
><br>
> only your first statement is correct. The second one could be<br>
> correct if<br>
> you could pair the trials, but it would be very rare that you would<br>
> want<br>
> to do this (since trials are recorded at different times and are<br>
> usually<br>
> not paired between conditions). Look up the help of the newtimef<br>
> function which allows computing differences between power between<br>
> different conditions and newcrossf which allows computing<br>
> difference<br>
> between phase coherence images.<br>
><br>
> Best,<br>
><br>
> Arno<br>
><br>
> Hsu, Shen-Mou wrote:<br>
> > Dear list-memebers,<br>
> ><br>
> > Suppose that I am interested in comparing two conditions A
and B<br>
> in terms of their power and phase coherence. I was wondering which<br>
> one of the following steps is more theoretically correct. 1. After<br>
> segmentation, calculate the EEG differences between the condition A<br>
> and B and then perform time-frequency analysis on the differences.<br>
> 2. After segmentation, perform time-frequency analysis on the EEG<br>
> data of the condition A and B respectively and then compute the<br>
> power or phase coherence differences between two conditions. Any<br>
> comments would be much appreciated.<br>
> ><br>
> > Many thanks,<br>
> ><br>
> > Shen-Mou Hsu<br>
> ><br>
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