<div dir="ltr">Dear Nenad,<div><br></div><div>If you average across trials that have same temporal structures that should be fine.</div><div><br></div><div>I haven't seen a gamma decomposed as a separate IC, but it has been always accompanied by theta. That means, if theta were not decomposed well, there would not be clear gamma found in ICs. There are several reasons I can think of to explain it... one is the low amplitude, second is the small local activation (i.e. not widely volume conducted), etc.</div>
<div><br></div><div>Makoto</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">On Mon, Jul 7, 2014 at 2:00 PM, Nenad Polomac <span dir="ltr"><<a href="mailto:polomacnenad@gmail.com" target="_blank">polomacnenad@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div><div>Hi everybody,<br><br></div>I am interested in evoked gamma band response. I would like to extract the independent components from my EEG data which represent this effect. My idea was to calculate the ICA on my 60 channel EEG single trials and then to average the time-courses each of the components over trials. Then on this evoked trial I would calculate time frequency with the Morlet wavelet and obtain evoke power each of components (freq wise baseline correction as well). Finally, those components that have in a particular time window increase in power relative to baseline would be considered as the one that represent gamma band response. I would use these info for the rejecting of all other components from the original (non averaged) ICA data. After that I would back project remaining (gamma representing) components into the channels. My question would be, is this ok to do from the mathematical point of view? I am particularly asking about the step where time-courses each of the components is averaged over trials. <br>
</div>I would really appreciate some opinions and experiences.<br><br></div>All the best!<span class="HOEnZb"><font color="#888888"><br><br></font></span></div><span class="HOEnZb"><font color="#888888">Nenad<br><div><div>
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-- <br><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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