yes, ica does not care whether data is epoched or continuous.<br>However, of course, the cleanliness and nature of the data given is crucial.<br>
<br><br><div class="gmail_quote">On Tue, Aug 16, 2011 at 9:10 AM, Maximilien Chaumon <span dir="ltr"><<a href="mailto:maximilien.chaumon@gmail.com">maximilien.chaumon@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
Thanks Ronald,<br>I understand your point with the dimensions.<br>I thought ICA does not care about time, though? So concatenated, epoched or not, the results should be the same, right?<br>Max<div><div></div><div class="h5">
<br><br><div class="gmail_quote">
2011/8/16 Ronald Phlypo <span dir="ltr"><<a href="mailto:Ronald.Phlypo@ugent.be" target="_blank">Ronald.Phlypo@ugent.be</a>></span><br><blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div bgcolor="#FFFFFF" text="#000000">
Dear Max,<br>
<br>
the problem lies in the maximally allowed number of components in
both decompositions. The first decomposition may allow for as many
sources as sensors (15 in your case). However, once 3 artefacts have
been removed, your data dimension reduces to 12, which allows to
estimate a maximum of 12 sources only. To circumvent this problem, I
suppose what the wiki means is to do local decompositions first
(trial by trial or epoch by epoch) and then concatenating the
trials/epochs again after their correction and before the second
"joint" decomposition. Since in this case the artefact removal is
nonlinear, it does not reduce the dimension of your concatenated
data.<br>
<br>
Hope this helps,<br><font color="#888888">
<br>
Ronald<br>
</font><br>
PS: you might also want to have a look at <a href="http://www.hindawi.com/journals/cin/2007/075079/cta/" target="_blank">http://www.hindawi.com/journals/cin/2007/075079/cta/</a>
where short time and long term windows are used jointly for artefact
removal. The text refers to literature on the mean duration of
electrophysiological processes to motivate this decision.<br>
<br>
Le 15/08/2011 18:09, Maximilien Chaumon a écrit :
<blockquote type="cite"><div><div></div><div>Hello all,<br>
<br>
I'm currently cleaning data before working with components.<br>
<ul>
<li>I cut my dataset into epochs</li>
<li>reject epochs where signal is bad</li>
<li>run an ICA</li>
<li>find blink and muscle components, reject them</li>
<li>run an ICA again, and look at my components.</li>
</ul>
... as I understood was suggested at the bottom of this page <a href="http://sccn.ucsd.edu/wiki/Chapter_01:_Rejecting_Artifacts" target="_blank">http://sccn.ucsd.edu/wiki/Chapter_01:_Rejecting_Artifacts</a><br>
<br>
Then the ICs look very nice but come in pairs of extremely similar
topographies with different time courses, as shown on <a href="http://oszilla.hgs.hu-berlin.de/public/2ICAs.png" target="_blank">this picture</a>.<br>
I am wondering what happened here. I can imagine that rejecting
components before running the second ICA is what went wrong... But
why did I read that on the wiki?<br>
<br>
Thanks a lot for any advice.<br>
Max<br>
<br>
<br>
<fieldset></fieldset>
<br>
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