[FieldTrip] problem with source reconstruction of ERP

[Zizlsperger Leopold]

Hi all,
I need your help with a problem with calculating the inverse solution in source reconstruction. I create source / volume conduction model using the FieldTrip default MRI and the tutorial documentation, my EEG electrodes align well, too. The problem appears when I try to process my functional timelocked data (demean=yes, covariance=yes): 
In my example the two datasets have the structure:

disp(EEG1_HC35_GA_JD_ICA_Coh5cov);
          avg: [32x7000 double]
          var: [32x7000 double]
         time: [1x7000 double]
          dof: [32x7000 double]
        label: {32x1 cell}
        trial: [314x32x7000 double]
       dimord: 'rpt_chan_time'
    trialinfo: [314x32 double]
          cfg: [1x1 struct]


disp(EEG1_HC35_GA_JD_ICA_Coh70cov);
          avg: [32x7000 double]
          var: [32x7000 double]
         time: [1x7000 double]
          dof: [32x7000 double]
        label: {32x1 cell}
        trial: [206x32x7000 double]
       dimord: 'rpt_chan_time'
    trialinfo: [206x32 double]
          cfg: [1x1 struct]

When I try to do the sourceanalysis by:

cfg        = [];
cfg.method = 'mne';
cfg.elec = elec_aligned;
cfg.grid   = leadfield;
cfg.vol    = vol;
cfg.mne.prewhiten = 'yes';
cfg.mne.lambda    = 3;
cfg.mne.scalesourcecov = 'yes';
sourceCoh5  = ft_sourceanalysis(cfg, EEG1_HC35_GA_JD_ICA_Coh5cov);
sourceCoh70 = ft_sourceanalysis(cfg, EEG1_HC35_GA_JD_ICA_Coh70cov);

save source sourceCoh5 sourceCoh70;

 I get the error:

the input is timelock data with 32 channels and 7000 timebins
using headmodel specified in the configuration
using electrodes specified in the configuration
determining source compartment (3)
projecting electrodes on skin surface
combining electrode transfer and system matrix
creating dipole grid based on user specified dipole positions
using headmodel specified in the configuration
using gradiometers specified in the configuration
8196 dipoles inside, 0 dipoles outside brain
the call to "ft_prepare_sourcemodel" took 0 seconds
estimating current density distribution for repetition 1
using pre-computed leadfields: some of the specified options will not have an effect
Warning: computing a unregularised minimum norm solution. This typically does not work
due to numerical accuracy problems 
> In minimumnormestimate at 150
  In ft_sourceanalysis at 856
??? Error using ==> mtimes
Inner matrix dimensions must agree.

Error in ==> minimumnormestimate at 226
  mom = w * dat;

Error in ==> ft_sourceanalysis at 856
        dip(i) = minimumnormestimate(grid, sens, vol, squeeze_avg, optarg{:}); 



Is this due to the different trial numbers of the datasets or does it point to another problem?
Thanks in advance
Best

Leo
RWTH Aachen Neurology






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