<div dir="ltr">Diego, can I ask you another advice- this time more conceptually? I am playing with the ICA now and experience, that I get very different components depending on the artifact detection that I do beforehand. So my idea (due to the literature) was, that the ICA works better on already cleaned data. Now, as I want to do a frequency analysis afterwards, I did not want to reject parts of trials. Therefore I deleted a relatively big amount of trials in which I found muscle artifacts/drifts (Say 25% of the whole amount of trials). However, in fact I see that the ICA then does not give me easily to interpret components anymore - actually the results are better (that is easier to interpret which is artifact, which not) if I include all trials. If I only reject parts of the trials it gets even a bit better. So my question is: Shell I a) do the (stricter) artifact detection rather after the ICA or b) perform it on data with parts of trials marked as bad - in which case I also ask: can I then still reject those components in the uncleaned data (saved beforehand) so that I do not get problems with the frequency analysis afterwards...?! <div style>
Thanks a lot for your help!!! Katrin</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">2014-05-28 15:02 GMT+02:00 KatrinH Heimann <span dir="ltr"><<a href="mailto:katrinheimann@gmail.com" target="_blank">katrinheimann@gmail.com</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Wonderfull! Thanks Diego!!!!<div>Cheers k</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">
2014-05-28 14:24 GMT+02:00 Lozano Soldevilla, D. (Diego) <span dir="ltr"><<a href="mailto:d.lozanosoldevilla@fcdonders.ru.nl" target="_blank">d.lozanosoldevilla@fcdonders.ru.nl</a>></span>:<div><div class="h5"><br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div style="font-family:Times New Roman;font-size:12pt;color:#000000"><font size="3">Hi Katrin,</font><div style="color:rgb(0,0,0);font-family:'Times New Roman';font-size:12pt">
<br></div><div style="color:rgb(0,0,0);font-family:'Times New Roman';font-size:12pt"><span style="font-size:12pt">First, to display the independent components:</span></div><div style="color:rgb(0,0,0);font-family:'Times New Roman';font-size:12pt">
<span style="font-size:12pt">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span></div><div><div><div>cfg = [];</div><div>cfg.layout = 'CTF151.lay'; % specify the layout file that should be used for plotting</div><div>cfg.viewmode = 'component'</div>
<div>ft_databrowser(cfg, comp)</div></div><div><br></div><div>Take a look to the following example script:</div><div><a href="http://fieldtrip.fcdonders.nl/example/use_independent_component_analysis_ica_to_remove_eog_artifacts" target="_blank">http://fieldtrip.fcdonders.nl/example/use_independent_component_analysis_ica_to_remove_eog_artifacts</a></div>
<div><br></div><div>Second, you'll have to compute the power spectrum for each independent component with ft_freqanalaysis:</div><div><br></div><div>%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</div><div><div>cfg = [];</div>
<div>cfg.output = 'pow';</div><div>cfg.channel = 'all';%compute the power spectrum in all ICs</div><div>cfg.method = 'mtmfft';</div><div>cfg.taper = 'hanning';</div>
<div>cfg.foi = 2:2:30;</div><div>freq = ft_freqanalysis(cfg, comp);</div><div><br></div><div>And you can plot the spectra:</div><div><br></div><div>%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</div><div>nsubplots = 25;</div>
<div>nbyn = sqrt(nsubplots);% sqrt(nsubplots) should not contain decimals, type doc subplot</div><div><br></div><div>Nfigs = ceil(size(comp.topo,1)/nsubplots);</div><div>tot = Nfigs*nsubplots;</div><div><br></div><div>rptvect = 1:size(comp.topo,1);</div>
<div>rptvect = padarray(rptvect, [0 tot-size(comp.topo,1)], 0,'post');</div><div>rptvect = reshape(rptvect,nsubplots,Nfigs)';</div><div><br></div><div>for r=1:size(rptvect,1);</div><div> figure;set(gcf,'units','normalized','outerposition',[0 0 1 1]);%full screen</div>
<div> k=0;</div><div> for j=1:size(rptvect,2);</div><div> if~(rptvect(r,j)==0);</div><div> k=k+1;</div><div> cfg=[];</div><div> cfg.channel = rptvect(r,j);</div><div> subplot(nbyn,nbyn,k);ft_singleplotER(cfg,freq);</div>
<div> end</div><div> end</div><div>end</div></div><div><br></div>For the IC topos you'll follow the same logic as above but with:</div><div><br></div><div><div>figure</div><div>cfg = [];</div><div>cfg.component = [1:20]; % specify the component(s) that should be plotted</div>
<div>cfg.layout = 'GSN-HydroCel-129.sfp'; </div><div>cfg.comment = 'no';</div><div>ft_topoplotIC(cfg, comp)</div><div><br></div><div>I hope it helps</div><div><br></div><div>Diego</div><hr style="color:rgb(0,0,0);font-family:'Times New Roman';font-size:12pt">
<blockquote style="color:rgb(0,0,0);font-family:'Times New Roman';font-size:12pt;border-left-width:2px;border-left-style:solid;border-left-color:rgb(16,16,255);margin-left:5px;padding-left:5px"><b>From: </b>"KatrinH Heimann" <<a href="mailto:katrinheimann@gmail.com" target="_blank">katrinheimann@gmail.com</a>><br>
<b>To: </b>"FieldTrip discussion list" <<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>><br><b>Sent: </b>Wednesday, 28 May, 2014 12:59:38 PM<br><b>Subject: </b>[FieldTrip] ICA - Can I visualize Activity power spectrum of single components?<div>
<div><br><br><div dir="ltr">Dear all,<div>another question: </div><div>Is it possible to visualize the Activity power spectrum of the single components after an ICA by using ft_databrowser (or something else). I like this feature from EEG lab as I find it easier to detect artifactual components. </div>
<div>Thanks a lot for your help</div><div>Katrin</div><div><br></div></div>
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<span><font color="#888888"><br><br><br><font size="3">-- </font><br><div style="color:rgb(0,0,0);font-family:'Times New Roman';font-size:12pt"><span name="x"></span>PhD Student<br>Neuronal Oscillations Group<br>
Donders Institute for Brain, Cognition and Behaviour <br>Centre for Cognitive Neuroimaging<br>Radboud University Nijmegen <br>NL-6525 EN Nijmegen<br>The Netherlands<br><a href="http://www.ru.nl/people/donders/lozano-soldevilla-d/" target="_blank">http://www.ru.nl/people/donders/lozano-soldevilla-d/</a><span name="x"></span><br>
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