[FieldTrip] problem aligning MRI with gradiometer

Allison Connolly ting.ac at gmail.com
Fri Feb 11 22:19:33 CET 2011


I am trying to perform beamforming on some MEG data (148 channels). I have
the dicom files for the MRI, and I have converted them to .img and .hdr
files using Curry.
I am importing them into fieldtrip via

Then I manually declaring the fiducials with
cfg.method                  = 'interactive';
mrialign                    = ft_volumerealign(cfg, mri);

Then segmenting with
cfg = [];
cfg.write        = 'no';
[segment] = ft_volumesegment(cfg, mri);

Then creating the head model with
cfg = [];
cfg.smooth                  = 'no';
vol = ft_prepare_singleshell(cfg, segment);

Then creating the grid with
cfg                 = [];
cfg.grad            = freq.grad;
cfg.vol             = vol;
cfg.reducerank      = 'no';
cfg.channel                 = {'MEG','-TRIGGER','-RESPONSE',...
cfg.grid.xgrid              = [-10:0.5:15]; % adjust according to vol
cfg.grid.ygrid              = [-15:0.5:15]; % adjust according to vol
cfg.grid.zgrid              = [-10:0.5:15]; % adjust according to vol
[grid] = ft_prepare_leadfield(cfg);

I am importing my MEG data with
cfg = [];  % empty configuration
cfg.dataset                 = 'C:/MEG Study/Subjectd001/d001/Billy_180s/06@
-09 at -10@_19_41/4/c,rfhp0.1Hz';
cfg.trialfun                = 'trialfun_general';
cfg.trialdef.triallength    = 2;  % duration in seconds
cfg.trialdef.ntrials        = inf;  % number of trials, inf results in as
many as possible
cfg                         = ft_definetrial(cfg);

% preprocess the data
cfg.channel                 = {'MEG','-TRIGGER','-RESPONSE',...
    '-GzyA','-GzxA','-MxaA','-MyaA','-MzaA','-E1','-E2','-E3','-E4'}; %read
all MEG channels except those with '-'
cfg.lpfilter                = 'yes';
cfg.lpfreq                  = 200;
cfg.bsfilter                = 'yes'; %60 Hz noise
cfg.bsfreq                  = [58 62];

data = ft_preprocessing(cfg);

In the end, when I go to plot them all on the same graph, the head model
seems to be 100 times larger than the gradiometer sensors (they appear as a
small ball in the middle of the head). I've tried adjusting the grad.unit
parameter from 'm' to 'cm', but it doesn't help the downstream frequency,
leadfield, and source analysis.

Can someone tell me how to ensure the gradiometer and mri/grid are on the
same scale so I can be sure I have the right model for my beamforming?

Thank you,
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