[FieldTrip] Strange MNE source reconstruction results

Jane Tan Jane.Tan at murdoch.edu.au
Tue Feb 19 16:24:39 CET 2019


Hi Jan-Mathijs,


Changing the interpmethod was indeed helpful. Thank you!

Cheers,
Jane

________________________________
From: fieldtrip <fieldtrip-bounces at science.ru.nl> on behalf of Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl>
Sent: Tuesday, 19 February 2019 10:07:47 PM
To: FieldTrip discussion list
Subject: Re: [FieldTrip] Strange MNE source reconstruction results

Hi Jane,

You may want to adjust the cfg.interpmethod in your call to ft_sourceinterpolate.

Or alternatively, don’t use ft_sourceinterpolate, and use cfg.method = ‘surface’, in ft_sourceplot

Happy computing and good luck,

Jan-Mathijs



J.M.Schoffelen, MD PhD
Senior Researcher, VIDI-fellow - PI, language in interaction
Telephone: +31-24-3614793
Physical location: room 00.028
Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands



On 19 Feb 2019, at 14:57, Jane Tan <Jane.Tan at murdoch.edu.au<mailto:Jane.Tan at murdoch.edu.au>> wrote:

Dear community,

I am trying to run source reconstruction on EEG data using minimum source estimation, but have gotten very strange-looking results. The ortho view (via ft_sourceplot) shows source activity "shooting" from within the cortex to outside of the head. I have attached a screen capture. I've been trying to find out what's wrong, but I can't seem to find anything amiss. I initially thought it might be an issue with the leadfield, but I use the BEM headmodel and sourcemodel ft templates for the leadfield calculation, and have checked that the sensors (EGI 128) are properly aligned to the headmodel using ft_plot_sens, so I don't think the problem lies with the leadfield.  I don't think that it is due to the dataset as well, because previous source reconstructions with beamformers resulted in normal-looking sourceplots.. I'm really at a loss right now, and would really appreciate any suggestions or advice.

My code:

% Getting noise-covariance
cfg = [];
cfg.covariance = 'yes';
cfg.covariancewindow = 'prestim'
tlckSS = ft_timelockanalysis(cfg, dataSS_epoched);

% Leadfield
sourcemodel=ft_read_headshape('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template\sourcemodel\cortex_8196.surf.gii');
cfg                 = [];
cfg.elec            = elec_aligned; %aligned to BEM headmodel
cfg.grid            = sourcemodel;   % FROM FT TEMPLATES
cfg.headmodel       = vol; %BEM headmodel from FT templates
leadfield           = ft_prepare_leadfield(cfg);

% Minimum norm estimation
cfg               = [];
cfg.method        = 'mne';
cfg.grid          = leadfield;
cfg.headmodel     = vol;
cfg.elec          = elec_aligned;
cfg.mne.prewhiten = 'yes';
cfg.mne.lambda    = 3;
cfg.mne.scalesourcecov = 'yes';
sourceSS          = ft_sourceanalysis(cfg,tlckSS);



% Loading single_subj_T1 MRI template
mri = ft_read_mri('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template \anatomy\single_subj_T1_1mm.nii');

% Reslice the MRI to align voxel axes with the head coordinate axes
mri = ft_volumereslice([], mri);


%Interpolate the source to the MRI
cfg            = [];
cfg.downsample = 2;
cfg.parameter  = 'pow';
sourceSSInt    = ft_sourceinterpolate(cfg, sourceSS , mri);


%Plotting
cfg = [];
cfg.method        = 'ortho';
cfg.funparameter  = 'pow';
cfg.latency       = [0.2 0.4]; %to specify time range in seconds
cfg.avgovertime   = 'yes'; % for time range
ft_sourceplot(cfg, sourceSSInt);


<pastedImage.png>




Best regards,

Jane


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