[FieldTrip] combining gradiometer/magnetometer sensors - neuromag data

Thomas Hartmann thomas.hartmann at th-ht.de
Wed May 10 10:07:23 CEST 2017


i would suggest updating to a recent fieldtrip version. combining mags 
and grads has been implemented there and you basically do not need to do 
any extra steps. there are just these three pitfalls that you need to 
pay attention to because it might lead to wrong results:

 1. make sure that you put in the original data. i.e. no prescaling etc.
    also make sure that you have not modified the .tra matrix of your
    grad structure.
 2. always compute your own leadfield. i.e. always use
    ft_prepare_leadfield to compute the forward model and don't have it
    done by ft_sourceanalysis. i don't know if this is absolutely
    necessary but as the ft_prepare_leadfield step is the one in which
    the actual pitfalls are, i would strongly suggest you do it
    separately to have maximum control!
 3. all the data going into ft_prepare_leadfield MUST BE in meters! i.e.:
     1. the grid mus be either created directly in meters of converted
        to meters by using ft_convert_unit
     2. the grad structure of your data must have been converted to
        meters. this is something you must do manually as according to
        my experience, fieldtrip does not take care of it. additionally,
        the default grad returned by ft_read_sens (and thus the one
        placed in your data structure) is in centimeters! so, it is a
        good idea to do something like this: data.grad =
        ft_convert_data(data.grad, 'm'); right after getting your data
        via ft_preprocessing!
     3. if you provide your grad structure in the cfg structure, also
        make sure that it is in meters.

the meters stuff is really extremely important!!! if your units are 
wrong, you are going to end up with wrong source projections and will 
not get an error message!!!

if you see some fieldtrip output like: "converting XXX to cm", your 
results will be wrong!

if you take care of all that, fieldtrip does the scaling automatically 
based on the distance between the two parts of each gradiometer.


Am 10.05.2017 um 09:33 schrieb Klink-3, N.E.C. van:
> Hi Andria,
> We have been struggling with the same problem, also using a 
> 306-channel Neuromag system. We ended up correcting for the scale 
> difference between magnetometer and gradiometer signals (i.e. noise 
> 5e-15T vs 5e-13T/m). So we multiplied the signals of the magnetometers 
> and the leadfield values of the magnetometers by a factor 100. This 
> gave us the best result.
> Kind regards,
> Nicole
> *Van:*fieldtrip-bounces at science.ru.nl 
> [mailto:fieldtrip-bounces at science.ru.nl] *Namens *Andria Pelentritou
> *Verzonden:* 10 mei 17 1:52
> *Aan:* fieldtrip at science.ru.nl
> *Onderwerp:* [FieldTrip] combining gradiometer/magnetometer sensors - 
> neuromag data
> Greetings from Melbourne!
> We've been using fieldtrip (v-20160801) for a while now and we are 
> having issues when it comes to combining magnetometer and gradiometer 
> MEG sensors types during (LCMV) beamforming for the Elekta Neuromag 
> Triux 306-channel system. Beamforming the magnetometers or 
> gradiometers separately on auditory evoked data works well, but we 
> cannot successfully combine the two sensor types. We've played with 
> the cfg.coilaccuracy variable as advised in one of the tutorials with 
> no luck as there seem to be no obvious effects on the output. The 
> documentation provides very little information on the topic.
> What strategies would you recommend when trying to combine the 
> Neuromag 306-channel system magnetometer/gradiometer data?
> Many thanks in advance for your help and many more thanks for 
> releasing such a valuable toolbox!
> Warm regards
> Andria
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Dr. Thomas Hartmann

Centre for Cognitive Neuroscience
FB Psychologie
Universit├Ąt Salzburg
Hellbrunnerstra├če 34/II
5020 Salzburg

Tel: +43 662 8044 5109
Email: thomas.hartmann at th-ht.de

"I am a brain, Watson. The rest of me is a mere appendix. " (Arthur Conan Doyle)

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