[FieldTrip] combining gradiometer/magnetometer sensors - neuromag data

[Sarang S. Dalal]

Dear Andria and Nicole,

Combining sensor types (gradiometers and magnetometers, or MEG and EEG) is indeed something that is not documented, and there is not yet a unanimous agreement in the community about how to do this best.

But, I can suggest one simple solution that was discussed at a recent beamformer workshop hosted by the Aston MEG Centre in February. (I believe John Mosher made the initial suggestion.)

As you probably know, the covariance matrix is an essential ingredient to constructing beamformer solutions. Different sensor types will have different scales and different noise properties, which then complicates the covariance between channels of different types.

So, one way around this is to zero out the ‘cross’ terms of the covariance matrix, i.e., set to 0 the elements of the covariance matrix that result from the product of a magnetometer channel and a gradiometer channel.  This can be accomplished with something like the following code:

timelock = ft_timelockanalysis(cfg, data);



[~,megmagidx]=intersect(data.label,ft_channelselection('MEGMAG',data.label));
[~,meggradidx]=intersect(data.label,ft_channelselection('MEGGRAD',data.label));



timelock.cov(meggradidx,megmagidx)=0;
timelock.cov(megmagidx,meggradidx)=0;


In my experience, this allows source reconstruction using all channels, with results at least as good as analyzing the channels separately. This is not to say that is the best possible solution, but it is a simple one that should work well!

Best wishes,
Sarang

On 10 May 2017, at 09:33, Klink-3, N.E.C. van <N.vanKlink-2 at umcutrecht.nl<mailto:N.vanKlink-2 at umcutrecht.nl>> wrote:

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> [mailto:fieldtrip-bounces at science.ru.nl] Namens Andria Pelentritou
Verzonden: 10 mei 17 1:52
Aan: fieldtrip at science.ru.nl<mailto: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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