Group Statistics for Source Space Data in SPM8
This is a basic script for group statistical analysis of source estimation results in SPM8. It uses previously computed source estimation results as input to the SPM8 function batch_spm_anova. You can visualise the results as "glass brains" using the Results function in the SPM8 GUI, or display them on a standard cortical surface using the Render->Display utility.
% to be run in SPM 8 EEG
% runs group statistics on files in "imgfiles", using batch_spm_anova.m
% output written into directory "outdir" (RFX)
% OH, Feb 2010
addpath /imaging/local/meg_misc; % for meg_batch_anova
% root directory for previously computed source stimation results
pathstem = '/YourDataPath/';
% output root directory for results
out_dir_stem = '/YourResultDirectory';
%% Specify data information for each subject
subjects{1} = {'meg10_0007', '101206'};
subjects{2} = {'meg10_0008', '101224'};
subjects{3} = {'meg10_0009', '101231'};
nr_ss = length(subjects);
%% Define contrasts (depends on how you named output of source estimation)
clear contrasts;
contrasts{1} = {'Mmacespm8_block1_raw_ssstf_raw_1_t100_200_f_7.nii', 'Mmacespm8_block1_raw_ssstf_raw_1_t100_200_f_8.nii', 'CON7vsCON8'}; % Condition 7 vs Condition 8
contrasts{2} = {'Mmacespm8_block1_raw_ssstf_raw_1_t100_200_f_1.nii', 'Mmacespm8_block1_raw_ssstf_raw_1_t100_200_f_2.nii', 'CON1vsCON2'}; % Condition 1 vs Condition 2
nr_contrasts = length( contrasts );
%% Compute Contrasts
for cc = 1:nr_contrasts, % contrast by contrast
clear imgfiles;
for ss = 1:nr_ss, % subject by subject
nr_conds = length( contrasts{cc} );
for con = 1:nr_conds-1, % condition by condition
imgfiles{1}{ss}(con,:) = fullfile( pathstem, subjects{ss}{1}, subjects{ss}{2}, contrasts{cc}{con} ); % define full filename
end;
end;
S = spm_get_defaults; % get SPM default analysis parameters
S.imgfiles = imgfiles; % files for this contrast
S.outdir = fullfile( out_dir_stem, contrasts{cc}{nr_conds} ); % output directory for this contrast
fprintf(1, '%s\n', S.outdir);
batch_spm_anova( S ); % run SPM random effects analysis
end;