[FieldTrip] neighbours

[Robert Oostenveld]

whoops, I now see that Jorn has already provided a much better and elaborate answer. Better pay attention to what he writes and ignore my quick reply.

Robert  


On 31 Aug 2012, at 9:50, Jörn M. Horschig wrote:

> Hi Nenad,
> 
> 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.
> 
> 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.
> 
> 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.
> 
> Best,
> Jörn
> 
> On 8/30/2012 10:33 AM, Nenad Polomac wrote:
>> Hi,
>> 
>> 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  FT_CHANNELREPAIR? In the case I leave data with 271 sensor, will those missing sensors influence neighbors configuration in the statistic and the source localisation analysis?
>> 
>> Thank you in advance!
>> 
>> Kind regards!
>> 
>> Nenad
>> 
>> 
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> 
> 
> -- 
> 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
> 
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