<div dir="ltr"><div class="gmail_extra"><div class="gmail_quote"><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 Ana,<br></blockquote><div> </div><div> If I understand correctly , we use ft_denoise_synthetic and ft_denoise_pca to reduce noise due to recording (e.g. environment noise , thermal noise... ) not the brain signal artefact (e.g eye blink). Normally ,I use these two functions in the very early stage . </div>
<div> </div><div> Best,</div><div> Haiteng</div><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">
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Message: 5<br>
Date: Thu, 3 Apr 2014 00:54:42 +0200 (CEST)<br>
From: "Todorovic, A." <<a href="mailto:a.todorovic@fcdonders.ru.nl">a.todorovic@fcdonders.ru.nl</a>><br>
To: FieldTrip List <<a href="mailto:fieldtrip@donders.ru.nl">fieldtrip@donders.ru.nl</a>><br>
Subject: [FieldTrip] denoising data<br>
Message-ID:<br>
<<a href="mailto:124252612.215995.1396479282885.JavaMail.root@monoceros.zimbra.ru.nl">124252612.215995.1396479282885.JavaMail.root@monoceros.zimbra.ru.nl</a>><br>
Content-Type: text/plain; charset=utf-8<br>
<br>
Dear 'trippers,<br>
<br>
I'm curious to hear your thoughts on how to best denoise data. What I'm doing is working, but I'd like to hear whether it's logical or reasonable.<br>
<br>
In particular, I have two issues. One is that I use ICA to remove blinks, so I have to fit denoising into a pipeline that incorporates ICA (which, I am guessing, works well only without including reference channels).<br>
<br>
The other is that I see there are two functions for denoising, ft_denoise_synthetic and ft_denoise_pca.<br>
<br>
In sum (1) I'm not really sure WHEN the best moment for denoising is, given that I use ICA, and (2) I don't understand when it's better to use ft_denoise_synthetic and when ft_denoise_pca. I do see that ft_denoise_pca has the option of preprocessing reference channels separately, which makes it easier to use after ICA.<br>
<br>
I used to know only about the first function, and my solution was to do ft_denoise_synthetic (using the 'G3BR' option) prior to the ICA. Then I would remove components which contain artifacts, and continue with making ERF/TFRs/whatever. This produces data that is somewhat cleaner than when I skip the denoising step.<br>
<br>
I was curious about the ft_denoise_pca when I saw it, so I tried running it on filtered, preprocessed data that I had after I rejected ICA components. [In the process of doing ICA, I used the ft_denoise_synthetic option, as above.] This produced a different TFR at the end of the road, which again looked cleaner. Significantly cleaner, actually, but N=1.<br>
<br>
Now I'm not sure if it was a logical step to use both denoising functions, and if it would have been a better idea to do things differently. I'd like to hear both whether something in the logic is wrong, and whether it's inelegant.<br>
<br>
Cheers,<br>
Ana<br>
<br>
<br>
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<br>
Message: 6<br>
Date: Thu, 3 Apr 2014 07:53:36 +0200<br>
From: Haiteng Jiang <<a href="mailto:haiteng.jiang@gmail.com">haiteng.jiang@gmail.com</a>><br>
To: <a href="mailto:fieldtrip@science.ru.nl">fieldtrip@science.ru.nl</a><br>
Subject: Re: [FieldTrip] Question on Cluster-based permutation tests<br>
on time-frequency data<br>
Message-ID:<br>
<CAHSK_TQ5v_dOD6iOaqiu=<a href="mailto:2%2BknQ6iHyZqSfyu0r2xvLessob65w@mail.gmail.com">2+knQ6iHyZqSfyu0r2xvLessob65w@mail.gmail.com</a>><br>
Content-Type: text/plain; charset="iso-8859-1"<br>
<br>
Dear Nithin,<br>
<br>
Cluster statistic works both for MEG and EEG data since the machinery<br>
is the same . You can organize the Non-FT in the Fieldtrip style.<br>
Please not that FT have a data structure (channel*frequency*time ), so you<br>
need to transpose your data matrix first. Besides , you also need to<br>
define the layout of your channels , then you know the neighbors of<br>
channels (see ft_prepare_neighbours) because clusters are formed on the<br>
basis of temporal, spatial and spectral adjacency. For more information,<br>
please have a look at the tutorial again<br>
<a href="http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq" target="_blank">http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq</a>.<br>
<br>
All<br>
the best,<br>
<br>
Haiteng<br>
<br>
<br>
<br>
<br>
><br>
> Message: 6<br>
> Date: Wed, 2 Apr 2014 10:23:01 -0400<br>
> From: "Nithin Krishna" <<a href="mailto:nkrishna@mprc.umaryland.edu">nkrishna@mprc.umaryland.edu</a>><br>
> To: "list, FieldTrip discussion" <<a href="mailto:fieldtrip@science.ru.nl">fieldtrip@science.ru.nl</a>><br>
> Subject: [FieldTrip] Question on Cluster-based permutation tests on<br>
> time-frequency data<br>
> Message-ID: <<a href="mailto:20140402T102301Z_155300170001@mprc.umaryland.edu">20140402T102301Z_155300170001@mprc.umaryland.edu</a>><br>
> Content-Type: text/plain; charset="utf-8"<br>
><br>
> Dear All,<br>
> I read the tutorial section on Cluster-based permutation tests on<br>
> time-frequency data as well as the Maris and Oostenveld, Journal of<br>
> Neuroscience Methods, 2007 report. I am interested in setting up a ERP<br>
> experiment on EEG data in this regard I like the procedure and processing<br>
> section of the tutorial, however I would like to know if there is any<br>
> section for EEG, I understand that megplanar is specific for MEG.<br>
> Also is it possible to use 3D matrix (TFR) (time, Freq channels ) non<br>
> feild trip output to run the cluster based permutation tests.<br>
> Looking forward<br>
> Nithin<br>
><br>
><br>
><br>
> --<br>
Haiteng Jiang<br>
PhD candidate<br>
Neuronal Oscillations Group<br>
Donders Institute for Brain, Cognition and Behaviour<br>
Centre for Cognitive Neuroimaging<br>
Radboud University Nijmegen<br>
<br>
Visiting address<br>
Room 2.32<br>
Donders Centre for Cognitive Neuroimaging<br>
Kapittelweg 29<br>
6525 EN Nijmegen<br>
the Netherlands<br>
<br>
Tel.: <a href="tel:%2B31%20%280%29243668291" value="+31243668291">+31 (0)243668291</a><br>
Web: <a href="https://sites.google.com/site/haitengjiang/" target="_blank">https://sites.google.com/site/haitengjiang/</a><br>
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</blockquote></div><br><br clear="all"><div><br></div>-- <br><div><div><font face="arial, helvetica, sans-serif">Haiteng Jiang</font></div><div><font face="arial, helvetica, sans-serif">PhD candidate</font></div><div><font face="arial, helvetica, sans-serif">Neuronal Oscillations Group</font></div>
<div><font face="arial, helvetica, sans-serif">Donders Institute for Brain, Cognition and Behaviour</font></div><div><font face="arial, helvetica, sans-serif">Centre for Cognitive Neuroimaging</font></div><div><font face="arial, helvetica, sans-serif">Radboud University Nijmegen</font></div>
<div><span style="line-height:18px;background-color:rgb(255,255,255)"><font face="arial, helvetica, sans-serif"><br></font></span></div><div><span style="line-height:18px;background-color:rgb(255,255,255)"><font face="arial, helvetica, sans-serif">Visiting address</font></span></div>
<div><div style="text-align:left;background-color:rgb(255,255,255)"><div><span style="line-height:18px"><font face="arial, helvetica, sans-serif">Room 2.32</font></span></div><div><span style="line-height:18px"><font face="arial, helvetica, sans-serif">Donders Centre for Cognitive Neuroimaging</font></span></div>
<div><span style="line-height:18px"><font face="arial, helvetica, sans-serif">Kapittelweg 29</font></span></div><div><span style="line-height:18px"><font face="arial, helvetica, sans-serif">6525 EN Nijmegen</font></span></div>
<div><span style="line-height:18px"><font face="arial, helvetica, sans-serif">the Netherlands</font></span></div><div><span style="line-height:18px"><font face="arial, helvetica, sans-serif"><br></font></span></div></div>
</div><div><font face="arial, helvetica, sans-serif"> Tel.: +31 (0)243668291</font></div></div><div><font face="arial, helvetica, sans-serif"> Web: <a href="https://sites.google.com/site/haitengjiang/" target="_blank">https://sites.google.com/site/haitengjiang/</a></font></div>
</div></div>