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<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>
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<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>