[FieldTrip] center of sphere artefact

[Johanna Zumer]

Dear Frederic,

I see that you have computed the 'noise' (from
cfg.lcmv.projectnoise='yes').  You can often use this output to remove the
center of sphere artifact to which you refer.  Have you tried this (i.e.
described here
http://fieldtrip.fcdonders.nl/tutorial/beamformer#neural_activity_index )
and does this help?

Also, how much is the rank of the covariance matrix (i.e. cov_data.cov)
reduced relative to number of sensors you have?  In other words, if
length(indx) is much less than the number of sensors, then you may need a
cfg.lcmv.lambda greater than 5%.

Best,
Johanna

2012/5/8 Frederic Roux <fredericroux at hotmail.de>

>  Dear all,
>
> I was looking at my lcmv-beamformer maps of ~200 Sec of
> eyes closed resting state MEG activity and wondering if
> what I was seeing is the center of sphere artefact.
>
> The code I used is:
>
> %filtering of the data
> cfg = [];
> cfg.bpfilter = 'yes';
> cfg.bpfilttype = 'but';
> cfg.bpfreq = [5 45];
> cfg.bpfiltord = 4;
> cfg.bpfiltdir = 'twopass';
>
> [meg_data] = ft_preprocessing(cfg,meg_data);
>
> %PCA to extract components with max explained variance
> [cf,pcs,vexp] = princomp(meg_data.trial{1},'econ');
> pexp = 100*vexp/sum(vexp);
> indx = find(cumsum(vexp) <=90);
> meg_data.trial{1} = (pcs(:,indx)*cv(:,indx)')';
>
> % computing the covariance matrix
> cfg = [];
> cfg.channel = {'MEG'};
> cfg.covariance = 'yes';
> cfg.pad = 'maxperlen';
> cfg.sgncmb = {'MEG' 'MEG'};
> cfg.removemean = 'yes';
>
> [cov_data] = ft_timelockanalysis(cfg,meg_data);
>
> %LCMV beamformer
> cfg = [];
> cfg.channel = {'MEG'};
> cfg.grid = grid_data;
> cfg.vol = hdm;
> cfg.method = 'lcmv';
> cfg.grid.dim = [Nx Ny Nz];
>
> cfg.lcmv.fixedori = 'no';
> cfg.lcmv.lambda = '5%';
> cfg.lcmv.projectnoise = 'yes';
> cfg.lcmv.keepfilters = 'yes';
> cfg.lcmv.projectmom = 'no';
> cfg.lcmv.keepmom = 'no';
> cfg.lcmv.reducerank = 2;
> cfg.lcmv.normalize = 'yes';
>
> [bf] = ft_sourceanalysis(cfg,cov_data);
>
> %make power unit invariant
> bf.avg.pow = bf.avg.pow./max(bf.avg.pow);
>
> Since I don't have enough experience to judge about that
> I wanted to ask if anybody out there with experience
> could tell me their opinion.
>
> The grid was computed using an inwardshift of -0.5 and a grid
> resolution of 2.5 mm. The head model using the ft_prepare_singleshell.
>
> Any help,advice, comments or suggestions would be highly appreciated.
>
> Best,
> Fred
>
>
>
> --
> Frédéric Roux, PhD student
> Department of Neurophysiology
> Max Planck Institute for Brain Research
> D-60529 Frankfurt am Main
> Frederic.Roux at brain.mpg.de
> +49(0)69630183225
>
>
>
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>
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