Source analysis on timelockdata

Christine Gruetzner christine.gruetzner at GOOGLEMAIL.COM
Tue Dec 22 17:00:56 CET 2009 

Hi everyone,

I got a problem with performing source analysis (minimum norm estimate) on
timelockdata, and I would be very glad if anyone could help me out!
So far, I've done the following steps (using fieldtrip version 20091221):

1) Compute timelockanalysis with cfg.latency = [0.05 0.4] and baseline
correction for condition 1 and 2
2) Source analysis with cfg. method = 'mne' on the timelock data, using
inverse grids
In the output from the source analysis I have avg.pow = 4560x211 for each
subject (211 = number of time samples)

The problem is that I can't compute sourcegrandaverage (see code below) on
these data (error at sourcegrandaverage at 178, dat(:,i) = tmp(:));
I already tried to put the single datasets directly into sourcestatistics,
but this doesn't work either (error: "the function requires source or volume
data as input")

I guess the problem is caused by the time dimension in the timelock data -
does anyone have an idea how to handle this information in source analysis /
source grandaverage / source statistics?

Best
Christine

%-------------------------------------------------
% Code for Source Statistics

datapath =
'/data/home1/ctillman/data/MooneyMEEGFieldtripAnalysis/ERF/Pilot/MNE/';

DataFaceFiles = {
'ERF_Task_BaseCorr_PreprocNew1secbase_ABA04_MooneyFacesMEEG_20070625_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_BBA06_MooneyFacesMEEG_20080318_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_CSA25_MooneyFacesMEEG_20070912_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_FSA04_MooneyFacesMEEG_20070529_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_GDE03_MooneyFacesMEEG_20071002_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_IFS20_MooneyFacesMEEG_20070809_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_IKE28_MooneyFacesMEEG_20070329_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_JHA07_MooneyFacesMEEG_20070327_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_JPA05_MooneyFacesMEEG_20080403_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_MKA21_MooneyFacesMEEG_20070711_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_MMA07_MooneyFacesMEEG_20070706_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_PSS16_MooneyFacesMEEG_20080312_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_SNI05_MooneyFacesMEEG_20080313_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_TWS22_MooneyFacesMEEG_20070831_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_UWA31_MooneyFacesMEEG_20070914_0_cond_1SRC_MNE_0p5iws_lambda05.mat';
};

DataInvertedFiles = {
'ERF_Task_BaseCorr_PreprocNew1secbase_ABA04_MooneyFacesMEEG_20070625_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_BBA06_MooneyFacesMEEG_20080318_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_CSA25_MooneyFacesMEEG_20070912_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_FSA04_MooneyFacesMEEG_20070529_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_GDE03_MooneyFacesMEEG_20071002_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_IFS20_MooneyFacesMEEG_20070809_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_IKE28_MooneyFacesMEEG_20070329_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_JHA07_MooneyFacesMEEG_20070327_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_JPA05_MooneyFacesMEEG_20080403_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_MKA21_MooneyFacesMEEG_20070711_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_MMA07_MooneyFacesMEEG_20070706_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_PSS16_MooneyFacesMEEG_20080312_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_SNI05_MooneyFacesMEEG_20080313_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_TWS22_MooneyFacesMEEG_20070831_0_cond_4SRC_MNE_0p5iws_lambda05.mat';
'ERF_Task_BaseCorr_PreprocNew1secbase_UWA31_MooneyFacesMEEG_20070914_0_cond_4SRC_MNE_0p5iws_lambda05.mat';

};

template =
load('/data/home1/ctillman/data/MooneyMEEGFieldtripAnalysis/Beamforming/MNIgrids/Grids0p5_170109/MNItemplate_170109_-0p5iws.mat');
Nx = length(template.template_grid.xgrid);
Ny = length(template.template_grid.ygrid);
Nz = length(template.template_grid.zgrid);
%--------------------------------------------------------------------------

for i = 1:length(DataFaceFiles)
    fullname1 = strcat(datapath,DataFaceFiles{i,1});
    DataFace{i} = load(fullname1);
end

for i = 1:length(DataInvertedFiles)
    fullname2 = strcat(datapath,DataInvertedFiles{i,1});
    DataInverted{i} = load(fullname2);
end

%--------------------------------------------------------------------------
% Fixing the structure properties
% Absolute power difference
for l = 1:length(DataFaceFiles)


   DataFace{l}.DataERFOut.xgrid = template.template_grid.xgrid;
   DataFace{l}.DataERFOut.ygrid = template.template_grid.ygrid;
   DataFace{l}.DataERFOut.zgrid = template.template_grid.zgrid;
   DataFace{l}.DataERFOut.dim = [Nx Ny Nz];
   DataFace{l}.DataERFOut.pos = template.template_grid.pos;
   DataFace{l}.DataERFOut.inside = template.template_grid.inside;
   DataFace{l}.DataERFOut.outside = template.template_grid.outside;
   DataFace{l} = DataFace{l}.DataERFOut;

end

for l = 1:length(DataInvertedFiles)


    DataInverted{l}.DataERFOut.xgrid = template.template_grid.xgrid;
    DataInverted{l}.DataERFOut.ygrid = template.template_grid.ygrid;
    DataInverted{l}.DataERFOut.zgrid = template.template_grid.zgrid;
    DataInverted{l}.DataERFOut.dim = [Nx Ny Nz];
    DataInverted{l}.DataERFOut.pos = template.template_grid.pos;
    DataInverted{l}.DataERFOut.inside = template.template_grid.inside;
    DataInverted{l}.DataERFOut.outside = template.template_grid.outside;
    DataInverted{l} = DataInverted{l}.DataERFOut;

end

% Compute grand average for Condition 1 and 2
cfgGA = [];
cfgGA.keepindividual = 'yes';
% cfg.parameter = 'pow';
% create command strings for the computation:
commandstr1 = strcat ('DataGAFace', '= sourcegrandaverage(cfgGA');
commandstr2 = strcat ('DataGAInverted',  '= sourcegrandaverage(cfgGA');

  for l = 1 : length(DataFace)
    commandstr1 = strcat(commandstr1, ',DataFace{', num2str(l) , '}');
end
% finalize command strings
commandstr1 = strcat(commandstr1,');');
eval(commandstr1) % yields DataGADiff;

for l = 1 : length(DataInverted)
    commandstr2 = strcat(commandstr2, ',DataInverted{', num2str(l) , '}');
end
% finalize command strings
commandstr2=strcat(commandstr2,');');
eval(commandstr2) % yields DataGADiff;

cfg = [];
cfg.dimord = 'voxel';
cfg.dim = [15 19 16];
nSubjects = length(DataFaceFiles);
a = [1:nSubjects];
b = ones(1,nSubjects);
cfg.design = [a a; b (2*b)];
cfg.uvar = 1; % "subject" is unit of observation
cfg.ivar = 2; % row
cfg.method = 'montecarlo';
cfg.correctm = 'fdr';
cfg.alpha = 0.05;
cfg.numrandomization = 6000;
cfg.parameter = 'pow';
cfg.statistic = 'depsamplesT';

sourceStat = sourcestatistics(cfg, DataGAFace, DataGAInverted);



-- 
Christine Grützner, geb.Tillmann
Max-Planck-Institut für Hirnforschung
Abt. Neurophysiologie
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

Phone: +49 (0)69/6301-83225
E-Mail: tillmann at mpih-frankfurt.mpg.de
http://www.mpih-frankfurt.mpg.de/global/Np/Staff/tillmann.htm

----------------------------------
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