Phantom Dipole on VectorView

[Masao Matsuhashi]

Dear Fieldtrip users (especialy the Neuromag users),

I want to use Fieldtrip to analyze my Vectorview data.
Fist I tried a phantom recording and performed an ECD analysis, but the 
result does not match. Please see the example below.  The difference 
within 5 mm may be ok, but the y-axis...
Would you please tell me what is wrong?
One concern may be that the Neuromag coordinate frame is different from 
CTF coordinate, but this does not matter if I do not try to overlay the 
source onto MRI, am I right? 
SSP significantly distorts the waveform of this huge field, so I am fine 
without it.

Thank you in advance,
Masao

Phantom Dipole #10 at (0.0, -4.86, 2.35)
Estimated position: (-0.598803 -6.67657 2.81002)
Raw data file: Dip10_1000nA_std_03_raw.fif
MATLAB Version 7.5.0.342 (R2007b)
fieldtrip-20071105

=================== Procedure ===============================
sRawFIFF_name='Dip10_1000nA_std_03_raw.fif';
pre=0.05;
post=0.1;

% create trial info
hdr = read_fcdc_header(sRawFIFF_name);
prep=round(pre*hdr.Fs);
postp=round(post*hdr.Fs);
data= read_fcdc_data(sRawFIFF_name,'chanindx',315);
data=reshape(data,numel(data),1);
trig = find(diff(data)>0);
trig = trig(2:end-1);

%read data
cfg             = [];
cfg.trl         = [trig-prep,trig+postp,repmat(-prep,size(trig))];
cfg.dataset     = sRawFIFF_name;      
cfg.datatype	= 'continuous';
cfg.blc         = 'yes';
cfg.blcwindow  	= [-pre 0];
cfg.channel    	= 'all';   % 'MEG' does not work
data = preprocessing(cfg);

% average
cfg = [];
avg = timelockanalysis(cfg, data);

% show waveform
figure
plot(1000*avg.time, avg.avg)  % convert time to ms
xlabel('time (ms)')
ylabel('field amplitude (T)')
axis tight
grid on

% fit a dipole
cfg             = [];
cfg.latency     = [0.019]; 
cfg.numdipoles  = 1;
cfg.gradfile    = sRawFIFF_name;
cfg.vol.o       = [0,0,0];  % in cm
cfg.vol.r       = 7;        % should not matter
cfg.grid.xgrid  = -7:1:7;
cfg.grid.ygrid  = -7:1:7;
cfg.grid.zgrid  = -1:1:8;
dip = dipolefitting(cfg, avg)

=================== Output ===================================
ntrl =
   111
reading and preprocessing
reading and preprocessing trial 1 from 111
reading and preprocessing trial 2 from 111
...
reading and preprocessing trial 111 from 111
the input is raw data with 315 channels and 111 trials
applying preprocessing options
averaging trials
averaging trial 1 of 111
averaging trial 2 of 111
...
averaging trial 111 of 111
the input is timelock data with 315 channels and 158 timebins
using headmodel specified in the configuration
reading gradiometers from file Dip10_1000nA_std_03_raw.fif
selected 306 channels
selected 1 topographies
900 dipoles inside, 1348 dipoles outside brain
scanning grid
scanning grid location 1/900
scanning grid location 2/900
...
scanning grid location 900/900
found minimum after scanning on grid point [0 -6 3]
                                                        First-order 
 Iteration  Func-count       f(x)        Step-size       optimality
     0           4         0.848031                        0.0232
     1          12         0.842257             10         0.0127  
     2          16         0.837597              1        0.00289  
     3          20         0.837204              1        0.00185  
     4          24         0.837115              1       0.000602  
     5          28         0.837106              1       0.000173  
     6          32         0.837105              1      4.07e-006  
     7          36         0.837105              1      1.86e-007  
     8          40         0.837105              1      1.04e-007  
     9          48         0.837105       0.407507      2.98e-008  
Optimization cannot make further progress:
 relative change in x less than options.TolX.
found minimum after non-linear optimization on [-0.598803 -6.67657 2.81002]
dip = 
     label: {1x306 cell}
       dip: [1x1 struct]
     Vdata: [306x1 double]
    Vmodel: [306x1 double]
      time: 0.0191
    dimord: 'chan_time'
      grad: [1x1 struct]
       cfg: [1x1 struct]
=================== End ======================================

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