[FieldTrip] EEG source reconstruction

[Johanna Zumer]

Dear Xiao,

The code doesn't look wrong at first glance.  However, with beamforming,
the pre-processing of the 'data' is just as important of a step, so be sure
you are using the optimal time windows for your research question, and
optimal frequency filtering, if desired, etc.

Also, check that the units of data.hdr.elec is the same as the vol and
sourcemodel.    Also, is there a reason you use data_org.hdr.elec in one
instance, and the data.hdr.elec in another instance?

Best,
Johanna


2013/7/29 陈雪 <mengtongxiao at gmail.com>

> Dear all
>
> I do EEG source analyse,But I use the method as the follow got strong
> function connectivity from different brain areas.（eg.correlation）and
> strength is similar;
> I want konw  the code with source reconstruction is right?
> Or some stimulate can  prove the code that is right.
> (the VOL and sourcemode form template)
>
>
> cfg                   = [];
> cfg.covariance        = 'yes';
> cfg.vartrllength      = 2;
> cfg.covariancewindow  = 'all';
> timelock              = ft_timelockanalysis(cfg, data);
>
>   cfg                 = [];
>  cfg.channel            = {'EEG'};
> cfg.vol             = vol;
>  cfg.reducerank      = 3;
>  cfg.normalize  ='yes';
>  cfg.elec         = data_org.hdr.elec;
> cfg.grid =sourcemodel;
>  [grid]= ft_prepare_leadfield(cfg);
>
>
> cfg             = [];
> cfg.method      = 'lcmv';
> cfg.vol    = vol;
> cfg.grid  = grid;
> cfg.lcmv.fixedori = 'yes';
> cfg.elec         = data.hdr.elec;
> cfg.lcmv.keepfilter  = 'yes';
> cfg.lcmv.projectnoise = 'yes';
> source1         = ft_sourceanalysis(cfg, timelock);
>
> thanks in advance
> xiao
>
>
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