[FieldTrip] Seizure localization problems

Dr.-Ing. Matthias Dümpelmann matthias.duempelmann at uniklinik-freiburg.de
Thu Jun 23 14:51:56 CEST 2016

Dear Azeez,

thank you for your suggestion.

Just exchanging

cfg.method       = 'dics';


cfg.method       = 'eloreta';

resulted in a reasonable solution (see attachment).

I also get useful results using MUIC or sLORETA in the frequency domain as the methods are implemented in ASA.

This makes me even more suspicious, what is going wrong with the DICS algorithm.

Best regards,


Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Azeez Adebimpe
Gesendet: Thursday, June 23, 2016 11:08 AM
An: FieldTrip discussion list
Cc: Nino Epitashvili
Betreff: Re: [FieldTrip] Seizure localization problems

Hi Mathias,
I will suggest you try other method like eLORETA or MNE  first and compare the result.



On Thu, Jun 23, 2016 at 9:34 AM, Dr.-Ing. Matthias Dümpelmann <matthias.duempelmann at uniklinik-freiburg.de<mailto:matthias.duempelmann at uniklinik-freiburg.de>> wrote:
Dear colleagues,

we are trying to evaluate systematically the localization  of rhythmic activity at the onset of epileptic seizures in patients, who are subsequently evaluated with intracranial recordings.

We are trying to use DICS but quite often receive results, which are obviously wrong. In the attached screenshots you can see the peace of EEG, which is evaluated and the localization result with a maximum in the cerebellum.

This a typical localization for the cases with obvious miss localizations. A further seizure with a similar EEG pattern was localized in the right temporal lobe, which matches the EEG pattern and also the intracranial findings.

Head model is generated with ASA, also the electrodes file is in the ASA format. The geometrical match of source points, head model and electrodes is checked using ft_plot_.... methods.

Here is the code sniplet relevant for the localization algorithm:

% Analysis frequency
SourceFrequency = 4.0

% read eeg, electrodes and volume conductor model
%[dat] = ft_read_data(filename);
hdr = ft_read_header(filename);
elec =  ft_read_sens(elecfile,  'fileformat','asa_elc');
headmodel = ft_read_vol(volumefilename,'fileformat','asa_vol');
mri = ft_read_mri(mrifilename, 'fileformat','asa_mri');

% eeg data preprocessing
cfgeeg.dataset = filename;
cfgeeg.continuous   = 'yes'
cfg.covariance       = 'yes';
cfg.covariancewindow = 'all';
cfg.demean = 'yes'

[data] = ft_preprocessing(cfgeeg);

% Freqanalysis for beamformer
cfg = [];
cfg.channel      = {'*'};
cfg.method       = 'mtmfft';
cfg.foilim     = [1 100];
cfg.tapsmofrq  = 4;
cfg.taper    = 'hanning';
cfg.output       = 'powandcsd';

% for common filter over conditions
powcsd_all      = ft_freqanalysis(cfg, data);

% Create leadfield grid
cfg                 = [];
cfg.channel         = elec.label;
cfg.elec            = elec;
cfg.headmodel       = headmodel;
cfg.dics.reducerank = 3; % default for MEG is 2, for EEG is 3
cfg.grid.resolution = 0.5;   % use a 3-D grid with a 0.5 cm resolution
cfg.grid.unit       = 'cm';
cfg.grid.tight      = 'yes';
[grid] = ft_prepare_leadfield(cfg);

% source analysis
cfg              = [];
cfg.channel      = elec.label;
cfg.method       = 'dics';
cfg.frequency    = SourceFrequency;
cfg.grid         = grid;
cfg.headmodel    = headmodel;
cfg.elec         = elec;
cfg.senstype     = 'EEG';
cfg.dics.keepfilter   = 'yes'; % We wish to use the calculated filter later on
cfg.dics.projectnoise = 'yes';
cfg.dics.lambda  = '0.3%';
source_raw = ft_sourceanalysis(cfg, powcsd_all);

I played with a couple of parameters like cfg.dics.lambda, but without success.

Do you have ideas how to improve our localization results ?

Thank you,


Breisacher Str. 64 · 79106 Freiburg
Telefon: +49 761 270-52410
matthias.duempelmann at uniklinik-freiburg.de<mailto:matthias.duempelmann at uniklinik-freiburg.de>


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