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<font face="Cambria">Hi James,<br>
Thank you for your quick response.<br>
The structure EEG.icaact is empty in my datasets. Do you know why
this might be?<br>
C<br>
</font><br>
On 08/09/2011 17:21, James Desjardins wrote:
<blockquote
cite="mid:20110908122137.jdq4spu6vwgkgcg8@webmail.brocku.ca"
type="cite">
<pre wrap="">Hi Cigir,
The following call to newtimef should compare the independent
component #1 of dataset #1 to dataset #2.
figure;
newtimef({ALLEEG(1).icaact(1,:,:), ALLEEG(2).icaact(1,:,:)}, ...
EEG.pnts, ...
[EEG.xmin EEG.xmax]*1000, ...
EEG.srate, ...
[3 0.5] , ...
'topovec', EEG.icawinv(:,1), ...
'elocs', EEG.chanlocs, ...
'chaninfo', EEG.chaninfo, ...
'baseline',[0], ...
'plotphase', 'off', ...
'padratio', 1);
James Desjardins
Technician, MA Student
Department of Psychology, Behavioural Neuroscience
Cognitive and Affective Neuroscience Lab
Brock University
500 Glenridge Ave.
St. Catharines, ON, Canada
L2S 3A1
905-688-5550 x4676
Quoting Cigir Kalfaoglu <a class="moz-txt-link-rfc2396E" href="mailto:c.kalfaoglu@sheffield.ac.uk"><c.kalfaoglu@sheffield.ac.uk></a>:
</pre>
<blockquote type="cite">
<pre wrap="">Hello,
A simple question with possibly a one line answer:
I am trying to calculate ERSP/ITC differences between conditions using
newtimef. However, I would like to use data from independent
components, rather than channels when doing so. I know pop_newtimef has
the option to do this via the key 'typeproc', but I couldn't get
pop_newtimef to work with two datasets.
Is there a way to analyse independent components using newtimef, or
alternatively, to use pop_newtimef with 2 datasets?
Thank you,
C
</pre>
</blockquote>
<pre wrap="">
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