[FieldTrip] gradiometer definitions after ft_megplanar

Till Schneider t.schneider at uke.uni-hamburg.de
Tue Dec 10 15:39:55 CET 2013


Hi Eelke,

just to get this issue straight. The correct way for creating an 
accurate forward model for MEG data after ICA artifact correction is to 
use the grad structure given by ft_rejectcomponent, right?
And the corrected grad stucture is only provided when the third input 
argument (i.e. the original data) is passed to ft_rejectcomponent? (e.g. 
data_clean = ft_rejectcomponent(cfg, comp, data_original), where comp is 
the result of ft_componentanalysis). Or is it sufficient to pass two 
input arguments (cfg and comp) to ft_rejectcomponent?

Best,
Till


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Till Schneider, PhD

Cognitive and Clinical Neurophysiology Group
Dept. of Neurophysiology and Pathophysiology
University Medical Center Hamburg-Eppendorf
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Am 09.12.13 09:16, schrieb Eelke Spaak:
> Hi Ana,
>
> Are you by any chance doing ICA followed by ft_rejectcomponent at some
> point before ft_megplanar? After rejecting a component, grad.chanpos
> and grad.chanori will contain only NaNs (as of some months ago
> indeed), as the channel positions are ill-defined at that point (i.e.
> each 'data'-channel is in fact a weighted mixture of the original,
> physical, MEG channels). Since ft_megplanar needs the channel
> positions, it can no longer operate on data after ft_rejectcomponent.
>
> However, there is an easy workaround: the original channel positions
> should quite nicely approximate the positions after
> ft_rejectcomponent. So, what I do is simply store the original
> data.grad somewhere, and then make sure to stick in the data just
> before ft_megplanar.
>
> Note that the reason why ft_rejectcomponent updates the grad is that
> creating an accurate forward model (for source reconstruction)
> requires accurate sensor information. Therefore it fills grad.chanpos
> with NaNs, while updating grad.coilpos etc. to reflect the new
> projection. So you should *not* use the original grad for source
> analysis after ft_rejectcomponent, in that case just use the updated
> one with the NaNs inside.
>
> Best,
> Eelke
>
> On 8 December 2013 22:44, Todorovic, A. <a.todorovic at fcdonders.ru.nl> wrote:
>> Dear 'trippers,
>>
>> I am attempting to do a TFR on planar gradient data. I first preprocess, then do ft_megplanar, then ft_freqanalysis, followed by ft_combineplanar. However, upon doing ft_megplanar, the grad.chanori field consists only of NaNs. I see that some changes were made a few months ago on how gradiometers are described, so I am wondering whether there are some changes I should now make to the cfg structure when doing the planar gradient transformation.
>>
>> This is how I normally do it:
>>
>>          cfg = [];
>>          cfg.planarmethod = 'sincos';
>>          cfg.channel = {'MEG'};
>>          cfg.trials = 'all';
>>          cfg.neighbours = neighbours; % neighbours=ft_prepare_neighbours(cfg,data)
>>          data_planar = ft_megplanar(cfg,data);
>>
>>
>> Alternatively, is there some workaround I could now implement to fix my already calculated TFR structures?
>>
>>
>> Cheers,
>> Ana
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
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