[FieldTrip] Whole-Brain Connectivity on parcellated data

[f.quandt at uke.de]

Dear Community,

I am working on a MEG dataset and would like to calculate task-related whole-brain connectivity in one specific frequency band. As I am running into memory issues, I would like to calculate the imaginary coherence on parcellated data (aal atlas). However, I am having trouble doing so, as after the parcellation the data structure/dimord is changed and ft_connectivityanalysis is not working anymore.

Does anyone have any suggestions? I was working along the tutorial “ Whole brain connectivity and network analysis” . Your help is much appreciated!

Many thanks,
Fanny


Here is the code I am using (Fieldtrip 20220216, macOs, Matlab R2021b) :


%% interpolate template sourcemodel and atlas
load(fullfile(templatedir, 'standard_sourcemodel3d8mm'));
atlas = ft_read_atlas(fullfile(templatedir, 'ROI_MNI_V4.nii'));

atlas = ft_convert_units(atlas,'mm');
sourcemodel = ft_convert_units(sourcemodel,'mm');

cfg = [];
cfg.interpmethod    = 'nearest';
cfg.parameter       = 'tissue';
sourceatlas = ft_sourceinterpolate(cfg, atlas, sourcemodel);
sourceatlas.pos=sourcemodel.pos;

%% frequency analysis of sensor level timeseries data
cfg=[];
cfg.method='mtmfft';
cfg.output='fourier';
cfg.keeptrials='yes';
cfg.tapsmofrq=tapsmofreq;
cfg.foi=foi;
cfg.polyremoval=1;

freq_all=ft_freqanalysis(cfg,data_all); % for common filter
freq=ft_freqanalysis(cfg,data_act); % activation
freqBase=ft_freqanalysis(cfg,data_base);% baseline


%% PPC
% calculate common filter
cfg=[];
cfg.frequency=freq.freq;
cfg.method='pcc';
cfg.sourcemodel=leadfield;
cfg.elec = freq_all.grad;
cfg.headmodel=headmodel;
cfg.rawtrials = 'yes';
cfg.keeptrials = 'yes';

cfg.pcc.lambda='10%';
cfg.pcc.projectnoise='yes';
cfg.pcc.keepfilter='yes';
source_all=ft_sourceanalysis(cfg,freq_all);

% apply filter
cfg.sourcemodel.filter = source_all.avg.filter;
source  = ft_sourceanalysis(cfg, freq);
sourceBase = ft_sourceanalysis(cfg, freqBase);

cfg=[];
source=ft_sourcedescriptives(cfg,source);
sourceBase=ft_sourcedescriptives(cfg,sourceBase);

% task related data
cfg = [];
cfg.parameter = 'avg.mom';
cfg.operation = '((x1-x2)./x2)';
sourceRel=ft_math(cfg,source,sourceBase);

% parcellation
sourceRel.pos=sourcemodel.pos;
sourceRel.dim=sourcemodel.dim;

cfg=[];
cfg.method='mean';
cfg.parameter='mom';
parc=ft_sourceparcellate(cfg,sourceRel,sourceatlas); % also does not work with source_all


sourceRel =
         freq: 75.8735
          dim: [20 25 22]
          pos: [11000×3 double]
        label: {272×1 cell}
          mom: {11000×1 cell}
       inside: [11000×1 logical]
    trialinfo: [235×10 double]
          cfg: [1×1 struct]

parc =
             freq: 75.8735
        cumtapcnt: [470×1 double]
            label: {1×116 cell}
              mom: [116×3×5170 double]
        momdimord: 'chan_ori_rpttap'
    brainordinate: [1×1 struct]
              cfg: [1×1 struct]


% Connectivity Analysis

        cfg=[];
        cfg.method='coh';
        cfg.complex='absimag';
        sourceConn=ft_connectivityanalysis(cfg,parc);

Error using getdimord (line 42)
field "crsspctrm" not present in data

Error in ft_connectivityanalysis (line 634)
    data.dimord = ['rpt_' getdimord(data, inparam)];

--

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