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<div class="moz-cite-prefix">Hi Makoto<br>
<br>
thank you so much for your suggestion.<br>
<br>
I took a look to std_envtopo. However, can you help me in
understanding how to use this plugin to extract a matrix with
size [number_of_channels, times], having in each row the erp of
the selected cluster ( e.g. cluster 2) projected on one channel
(e.g. on Fp1)?<br>
<br>
Thank you again<br>
<br>
Marco<br>
<br>
Il 12/06/2013 21:34, Makoto Miyakoshi ha scritto:<br>
</div>
<blockquote
cite="mid:CAEqC+SVUi7fxfy6HuoB=zudgcvQr700HAzGNqFLXg-UBR88KRg@mail.gmail.com"
type="cite">
<div dir="ltr">Dear Marco,
<div><br>
</div>
<div style="">Without reading your code, let me first ask if you
have tried std_envtopo(). That plugin is available since
version 11. After clustering, go to 'edit/plot cluster' and
you'll find the button in the bottom in the GUI. It seems that
is the function you need. If not, please let me know the
difference.</div>
<div style=""><br>
</div>
<div style="">Makoto</div>
</div>
<div class="gmail_extra"><br>
<br>
<div class="gmail_quote">2013/6/10 Marco Bellami <span
dir="ltr"><<a moz-do-not-send="true"
href="mailto:mrcbellami@gmail.com" target="_blank">mrcbellami@gmail.com</a>></span><br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">Hi All,<br>
<br>
I performed an ICA decomposition on my raw EEG data (for
each subject<br>
and condition). Then, I created a STUDY and a design and I
clustered ICs.<br>
Now, I want to calculate, for each cluster and condition of
my design,<br>
the projection of the ERP of the cluster on the channels and
I'd like to<br>
know if my approach is correct.<br>
First, I calculated the projection on the scalp of each
component of<br>
each cluster (using the icaproj function). Then, I averaged
the<br>
projected ERPs between the components of the same cluster:<br>
<br>
for example, let clust=1<br>
<br>
for cond = 1:total_conditions % choose a condition (from
STUDY.condition)<br>
<br>
% compute average cluster ERP projected on EEG
channels<br>
<br>
for ic =
1:length(STUDY.cluster(clust).allinds{cond}) % for<br>
each component in the cluster<br>
<br>
design_idx =
STUDY.cluster(clust).setinds{cond}(1,ic);<br>
setidx =
STUDY.design(design_number).cell(design_idx).dataset;<br>
%select the component<br>
comp =
STUDY.cluster(clust).allinds{cond}(1,ic);<br>
%load the dataset with the selected component<br>
[ALLEEG EEG CURRENTSET] = pop_newset(ALLEEG,
EEG,<br>
CURRENTSET,...<br>
'retrieve',setidx,'study',CURRENTSTUDY);<br>
<br>
winvs =<br>
ALLEEG(setidx).icawinv(:,:)*STUDY.cluster(clust).topopol(ic);<br>
% calculate the projection of the IC on all
channels<br>
prjics(:,:,ic)=icaproj2(mean(ALLEEG(setidx).data(:,:,:),3),pinv(winvs),comp);<br>
<br>
end;<br>
%average projection over trials<br>
prjclus=mean(prjics,3);<br>
<br>
Thanks,<br>
<br>
Marco<br>
<br>
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</blockquote>
</div>
<br>
<br clear="all">
<div><br>
</div>
-- <br>
<div dir="ltr">Makoto Miyakoshi<br>
Swartz Center for Computational Neuroscience<br>
Institute for Neural Computation, University of California San
Diego<br>
</div>
</div>
</blockquote>
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