[FieldTrip] Source reconstruction using DICS : poor results

[CHATEAUX Manon]

Dear FieldTrip community,

I am encountering problems in doing source reconstruction on  
coherences, computed between signal recorded by my 248 magnetometers  
(4D system) and the signal of a given EMG electrode that I called ¿FDI¿.

After preprocessing and cleaning my MEG and EMG data, I had a look at  
the distribution of the coherence values at the channel level. Around  
the beta band, I have quite clean results (See Figure 1).
Here is the script I used to obtain this figure, from my ¿data_CMC¿  
that is the clean data, ready to undergo CMC analysis :
cfg            = [];
cfg.output     = 'powandcsd'; %returns the power and the cross-spectra
cfg.method     = 'mtmfft';
cfg.taper      = 'hanning';
cfg.foilim     = [18 100];
cfg.keeptrials = 'no';
cfg.channel    = {'MEG' 'OP' 'FDI' 'ECD' 'FCD' 'TB' 'BB'};
cfg.channelcmb = {'MEG' 'MEG'; 'MEG' 'OP'; 'MEG' 'FDI'; 'MEG' 'ECD';  
'MEG' 'FCD'; 'MEG' 'TB'; 'MEG' 'BB'};
cfg.pad        = 'nextpow2';

freq_cross_spctr.FG   = ft_freqanalysis(cfg, data_CMC.FG);

Remark : I have 150 trials and they are very short, some are as short  
as about 100 ms which lead me to adapt cfg.foilim in order that it  
does not go under about 18Hz. Indeed, I calculated it so that we can  
have 2 periods of the minimum frequency in my shortest trial.

cfg = [];
cfg.xlim           = [CMC_cross_spectr.FG.freq(1,1)  
CMC_cross_spectr.FG.freq(1,5)]; %Between 18 and 26Hz
cfg.refchannel     = 'FDI';
cfg.layout         = lay;
cfg.colorbar       = 'yes';
cfg.parameter      = 'cohspctrm';
cfg.marker         = 'on';
cfg.dataname   = ['FG_' int2str(floor(CMC_cross_spectr.FG.freq(1,1)))  
'_' int2str(floor(CMC_cross_spectr.FG.freq(1,5))) '_' cfg.refchannel];
ft_topoplotER(cfg, CMC_cross_spectr.FG);

But now I want to precisely localize these coherences, in order to be  
able to answer my scientific question. I used the DICS beamformer  
method as advised by the tutorials. However, the reconstruction gives  
a terrible topographical mapping of the coherences that is not clean  
at all contrary to what I saw at the sensor level (Figure 2). Plus, it  
displays very low coherence values.

For information, I don¿t have any MRI of the participant. Thus, I used  
the fiducial positions, gathered just before the experiment started,  
and altered an MRI template so that it is aligned ¿ as well as  
possible ¿ to these recorded fiducials positions. (The participant  
moved less than 1mm during the experiment). Then I computed the  
segmented MRI and the head and source model from this manual alignment.
Here is the script that follows the computation of the forward model  
and that lead me to figure 2 :

cfg                 = [];
cfg.method          = 'dics';
cfg.refchan         = 'FDI';
cfg.frequency       = [freq_cross_spctr.FG.freq(1,1)  
freq_cross_spctr.FG.freq(1,5)];
cfg.headmodel       = hdm_cm;
cfg.sourcemodel   = sourcemodel;
cfg.grad                        = sensors_cm;
cfg.dics.reducerank      = 2; %default value for MEG. This is done to  
remove the weakest orientation.
cfg.dics.normalize       = 'yes'; %I use this because we don't have  
any baseline or second condition to compare to, for the moment
source_coh_lft      = ft_sourceanalysis(cfg, freq_cross_spctr.FG);

source_coh_lft.pos = sourcemodel.pos;
source_coh_lft.dim = sourcemodel.dim;

cfg              = [];
cfg.parameter    = 'coh';
cfg.interpmethod = 'nearest';
source_coh_int   = ft_sourceinterpolate(cfg, source_coh_lft,  
mri_realigned_to_headshape_m);

cfg               = [];
cfg.method        = 'surface';
cfg.surffile      = 'surffile.mat';
cfg.funparameter  = 'coh';
cfg.surfdownsample = 10; %gives more beautiful results
ft_sourceplot(cfg, source_coh_int);
colormap jet

MY QUESTIONS ARE THE FOLLOWING :
-        Why are the two maps so different ? Why are there such low  
coherence values in Figure 2? What am I missing?
-        Is there any way to improve the results of Figure 2?
-        Can I compute the CMC first at the sensor level and then do a  
reconstruction?
-        I am not confident with the method I used to align the  
template MRI to my recorded fiducials. Is there a more rigorous way to  
do it?

I am new to signal processing and especially to FieldTrip so any  
remark, suggestion or resource would be extremely helpful and highly  
appreciated!

Thank you very much in advance for your help and for the time you have  
spared reading through this message.

Manon Châteaux
Neuroscience Master Student
-- 
Manon CHATEAUX  | Normalienne Etudiante en dernière année du  
département de Biologie
manon.chateaux at ens-cachan.fr


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https://doi.org/10.1371/journal.pcbi.1002202