<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">hi nina,<div><br></div><div>did you validate the position by plotting them on the individuals MRI?</div><div>I mean the ones you define in xgrid, ygrid and zgrid.</div><div><br></div><div>when i project my data into source space to do e.g. time-frequencystuff i do:</div><div><div>cfg=[];</div><div>cfg.vol=vol;</div><div>cfg.grid.pos=rois; %%here is a difference to your code</div><div>cfg.grad=data.grad;</div><div>cfg.channel={'MEG'};</div><div><br></div><div>grid=prepare_leadfield(cfg);</div></div><div><br></div><div>then i continue with the sourceanalysis stuff.</div><div><br></div><div>good luck,</div><div>n</div><div><br><div><div>On 27.04.2010, at 14:23, Nina wrote:</div><br class="Apple-interchange-newline"><blockquote type="cite"><div lang="DE" link="blue" vlink="purple">
<div class="Section1"><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">Hi all,<o:p></o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial"><o:p> </o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">I am working on constructing a virtual sensor for my 122
Neuromag MEG data in order to compute time frequency analysis on this virtual
sensor. <o:p></o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">The results I am getting so far are not in line with
the sensor level data. On sensor level I see a very clear gamma response. It is
also present on source level in the frequency domain, using dics, however, the
time course of the source is not as strong and frequency confined on source
level. Does anybody have any ideas on what I might be doing wrong?<o:p></o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">In the following, I would like to explain what I have
done so far and what my problems are. I am attaching the script I used in text
format.<o:p></o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial"><o:p> </o:p></span></font></p><p class="MsoNormal"><b><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial;font-weight:bold">About the data set:<o:p></o:p></span></font></b></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">It contains trials of three different conditions.
These trials are of variable lengths (spread evenly over the conditions) and
there are not always the same number of trials in each condition. <o:p></o:p></span></font></p><p class="MsoNormal"><b><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial;font-weight:bold"><o:p> </o:p></span></font></b></p><p class="MsoNormal"><b><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial;font-weight:bold">What I have done so
far:<o:p></o:p></span></font></b></p>
<ol style="margin-top:0cm" start="1" type="1">
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">based on TFRs on
sensor level I chose each subject’s strongest gamma frequency <o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">for each subject, I
took this frequency (+/- 5 Hz) and calculated spatial filters for stimulation
and baseline periods, averaged over all three conditions using a DICS
beamformer <o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">for each voxel, the
ratio of poststimulus power to prestimulus power was computed</span></font><span lang="EN-GB"> </span><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial"><o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">from that I took the
voxel with maximum power increase and used it as my voxel of interest,</span></font><span lang="EN-GB"> </span><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial"><o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">for this voxel of
interest I calculated a new dipole grid with only one voxel. It is in the
same location as the strongest voxel from step 3.<o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">then I went back to
my functional data and used the FT function ‘timelockanalysis’
to compute the covariance matrices for all my sensors and trials (keeping
single trials), trying different time windows for covariance computation,
but always calculating power for the whole time period:</span></font><span lang="EN-GB"> </span><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial"><o:p></o:p></span></font></li>
<ol style="margin-top:0cm" start="1" type="a">
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">pre stimulus [-2 0]
(but using the whole trial for timelockanalysis; time = [-2 3], <o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">post stimulus [0 3]
(but using the whole trial for timelockanalysis; time = [-2 3],</span></font><span lang="EN-GB"> </span><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial"><o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">the whole time
period [-2 3],<o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">pre stimulus [-2 0]
(using only that time window for timelockanalysis; time = [-2 0], <o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">post stimulus [0 2]
(using only that time window for timelockanalysis; time = [0 2]<o:p></o:p></span></font></li>
</ol>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">the covariance
matrices were put into source analysis, again computing spatial filters
for the voxel of interest (using rawtrial = ‘yes’)<o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">NaNs, that were due
to different lengths of trials, in dipole moments resulting from source
analysis were removed<o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">then I put the
resulting dipole moments of the three directions (x,y,z) into a structure
that resembles that of preprocessed data<o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">time frequency
representations of power were calculated using a multitaper approach<o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">When looking at the
three directions (x,y,z,) separately in a time frequency plot, this gives
me</span></font><span lang="EN-GB"> </span><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial"><o:p></o:p></span></font></li>
<ol style="margin-top:0cm" start="1" type="a">
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">somehow meaningful
results for the covariance window being pre stimulus (5.a), however, they
are a lot weaker than on sensor level.</span></font><span lang="EN-GB"> </span><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:
Arial"><o:p></o:p></span></font></li>
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">no meaningful
results for the covariance window being post stimulus (5.b) or the whole
time period (5.c)<o:p></o:p></span></font></li>
</ol>
<li class="MsoNormal" style="mso-list:l0 level1 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">for 5. d/e relative
changes to baseline were calculated for each of the trials <o:p></o:p></span></font></li>
<ol style="margin-top:0cm" start="1" type="a">
<li class="MsoNormal" style="mso-list:l0 level2 lfo1"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:10.0pt;font-family:Arial">this gives me
somehow meaningful results, but very weak and not constrained to the
before found frequency ranges<o:p></o:p></span></font></li>
</ol>
</ol><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial"><o:p> </o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">Does anybody have experience with this kind of
analysis? Do you have any suggestions about which step might be causing these
troubles? <o:p></o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial"><o:p> </o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">Thank you all in advance for any help!<o:p></o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial"><o:p> </o:p></span></font></p><p class="MsoNormal"><font size="2" face="Arial"><span lang="EN-GB" style="font-size:
10.0pt;font-family:Arial">Nina<o:p></o:p></span></font></p><p class="MsoPlainText"><font size="2" face="Courier New"><span style="font-size:
10.0pt"><o:p> </o:p></span></font></p>
</div>
</div>
<p>----------------------------------</p><p>The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis.</p><p> <a href="http://listserv.surfnet.nl/archives/fieldtrip.html">http://listserv.surfnet.nl/archives/fieldtrip.html</a></p><p> <a href="http://www.ru.nl/fcdonders/fieldtrip/">http://www.ru.nl/fcdonders/fieldtrip/</a></p>
<span><virtualsensor.txt></span></blockquote></div><br></div></body></html><p>----------------------------------</p>
<p>The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis.</p>
<p> http://listserv.surfnet.nl/archives/fieldtrip.html</p>
<p> http://www.ru.nl/fcdonders/fieldtrip/</p>