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<div class="moz-cite-prefix">Hi Nenad,<br>
<br>
the question you are asking does not deserve a definite 'yes' or
'no'. In any case, note that when averaging over subjects, missing
sensors for one subject will be removed for all other subjects as
well. So, if you are talking about different missing sensors per
subject, an interpolation will definitely be a wise thing to do.
In case you choose for interpolating the missing channels, you can
try to check out the new spherical spline interpolation method
(see help ft_channelrepair) - theoretically that should result in
a quite good reconstruction. But the (standard) nearest neighbour
interpolation is fine as well.<br>
<br>
With respect to your second question: missing sensors will
influence the neighbour configuration depending on the method you
chose for neighbour selection. For the 'distance' and 'template'
method, each neighbouring channel of the missing will have one
sensor less (i.e. the missing one). The 'triangulation' method
will create triangle neighbour no matter how many channels you
have, so it will just ignore the whole in space. In any case, I'd
propose that you check out how satisfied you personally are with
the neighbours by calling ft_neighbourplot. Just last week, I
added the new option that if you use cfg.enableedit='yes', you can
interactively change the neighbourhood structure within the
neighbourplot. If I were you, I would start from the template
method. As an additional piece of information: I am currently
working on improving the neighbour templates, and will upload them
probably next week.<br>
<br>
All that advertised, let me also say that having 4 out of 275
sensors missing won't affect your statistics much. Here, it of
course depends on your region if interest, research question etc.
E.g. if you are interested in posterior alpha power, but miss four
temporal channels, there is no reason to worry. So, without
knowing what you are looking for and where the missing channels
are, I cannot give you a general advise what to do. As a last
remark, the sensitiviy of the statistics will of course be
influenced by missing sensors, but I doubt that it will matter
much. Btw, I am not quite sure how much the spherical spline
interpolation will buy you here, you might give it a try. I bet
that it will increase your sensitivity more than the nearest
neighbour approach, although both might result in rather low
increases. But this is just a general gut feeling rather than
anything I empirically validated.<br>
<br>
Best,<br>
Jörn<br>
<br>
On 8/30/2012 10:33 AM, Nenad Polomac wrote:<br>
</div>
<blockquote
cite="mid:CAEk4EpG2GVC3a31FSs3iA1mB-X1uFVYC=TjztQdus9_9dKNc-w@mail.gmail.com"
type="cite">Hi,
<div><br>
</div>
<div>I am analyzing data obtained on CTF MEG 275 system. However,
4 sensors are broken and data ended up with 271 sensor. So, my
question is should I interpolate the missing sensors with <span
style="background-color:rgb(247,249,250);color:rgb(51,51,51);font-family:Consolas,'Andale
Mono',Menlo,Monaco,monospace;font-size:12px;line-height:14.399999618530273px;text-align:justify;white-space:pre-wrap">
</span><font style="font-family:Consolas,'Andale
Mono',Menlo,Monaco,monospace;font-size:12px;line-height:14.399999618530273px;text-align:justify;white-space:pre-wrap;padding:0px;margin:0px;color:rgb(51,51,51)"
color="green"><a moz-do-not-send="true"
href="http://fieldtrip.fcdonders.nl/reference/ft_channelrepair"
title="" style="font-family:Consolas,'Andale
Mono',Menlo,Monaco,monospace;font-size:12px;line-height:14.399999618530273px;text-align:justify;white-space:pre-wrap;padding:0px;margin:0px;color:rgb(51,51,51)">FT_CHANNELREPAI</a><u>R</u>?
</font>In the case I leave data with 271 sensor, will those
missing sensors influence neighbors configuration in the
statistic and the source localisation analysis?</div>
<div><br>
</div>
<div>Thank you in advance!</div>
<div><br>
</div>
<div>Kind regards!</div>
<div><br>
</div>
<div>Nenad</div>
<br>
<fieldset class="mimeAttachmentHeader"></fieldset>
<br>
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</blockquote>
<br>
<br>
<pre class="moz-signature" cols="72">--
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team
P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands
Contact:
E-Mail: <a class="moz-txt-link-abbreviated" href="mailto:jm.horschig@donders.ru.nl">jm.horschig@donders.ru.nl</a>
Tel: +31-(0)24-36-68493
Web: <a class="moz-txt-link-freetext" href="http://www.ru.nl/donders">http://www.ru.nl/donders</a>
Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands</pre>
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