<div dir="ltr">Scott, would you like to comment?<div><br></div><div>Makoto</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">On Mon, Jul 28, 2014 at 3:13 AM, Eelke Spaak <span dir="ltr"><<a href="mailto:eelke.spaak@donders.ru.nl" target="_blank">eelke.spaak@donders.ru.nl</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Dear EEGlab list,<br>
<br>
I would like to perform Infomax ICA on a complex time-frequency<br>
representation of my data, as described in Anemüller, Sejnowski, &<br>
Makeig (2003) Neural Networks. Actually I am primarily using<br>
FieldTrip, but since FieldTrip just uses EEGlab's runica.m I thought<br>
this list was the best place to ask the following:<br>
<br>
If I input complex data (i.e. the Fourier coefficients for sliding<br>
time windows for a single frequency band) into runica.m, will the<br>
algorithm computed be the correct complex Infomax algorithm? I tried<br>
this and the output looks very reasonable (i.e. well-interpretable<br>
sensor maps, with primarily real and much weaker imaginary weights,<br>
consistent with what I think is expected for MEG data). But it would<br>
be great if this is confirmed by someone who actually knows about<br>
this.<br>
<br>
If complex ICA is not implemented in runica.m, maybe someone has<br>
thoughts on whether it would be easy to extend it such that it<br>
implements complex Infomax?<br>
<br>
Many thanks in advance!<br>
<br>
Best,<br>
Eelke<br>
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<div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br></div>
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