Updated source analysis tutorial

Author: vlitvak

docs/tutorials/beginners/MEEG/forward.png

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+
+### Group Statistics on Source Reconstructions
+
+Now we have a new set of 16$\times$<!-- -->3 GIfTI images for the power
+between 10-20Hz and 100-250ms for each subject for each condition after
+group-inversion, we can put them into the same repeated-measures ANOVA
+that we used above, i.e., the `batch_stats_rmANOVA_job.m` file. This can
+be scripted as (i.e, simply changing the output directories at the start
+from, e.g, `IndMSPStats` to `GrpMSPStats`).
+
+```matlab
+srcstatsdir{1} = fullfile(outpth,'MEEG','GrpMSPStats');
+srcstatsdir{2} = fullfile(outpth,'MEEG','GrpMNMStats');
+
+jobfile = {fullfile(scrpth,'batch_stats_rmANOVA_job.m')};
+
+for val = 1:length(srcstatsdir)
+    if ~exist(srcstatsdir{val})
+        eval(sprintf('!mkdir %s',srcstatsdir{val}));
+    end
+    
+    inputs  = cell(nsub+1, 1);    
+    inputs{1} = {srcstatsdir{val}};    
+    for s = 1:nsub
+        inputs{s+1,1} = cellstr(strvcat(spm_select('FPList',fullfile(outpth,subdir{s},'MEEG'),sprintf('^apMcbdspmeeg_run_01_sss_%d.*\.gii',val))));   
+    end
+    
+    spm_jobman('serial', jobfile, '', inputs{:});
+end
+```
+
+When it has run, press "Results" from the SPM Menu window and select the
+`SPM.mat` file in the relevant output directories. You will notice that
+the results for minimum norm have not changed much -- a lot of voxels
+remain significant after correction, but in a broadly distributed swathe
+of ventral temporal lobe. For the results in the `MEEG/GrpMSPStats`
+directory, there is a small anterior right temporal cluster that
+survives correction. But if you lower the threshold to $p<.001$
+uncorrected, you should see results like in
+Figure <a href="#multi:fig:15" data-reference-type="ref"
+data-reference="multi:fig:15">1.15</a>, which includes more focal
+regions in the ventral temporal lobe, and importantly, more such regions
+that for the individual MSP inversions the `MEEG/IndMSPStats` directory
+(demonstrating the advantage of group-based inversion).
+
+<figure id="multi:fig:15">
+<div class="center">
+<img src="../../../../assets/figures/manual/multi/figure15.png" style="width:150mm" />
+</div>
+<figcaption><em>Group SPM for Faces vs Scrambled power on cortical mesh
+between 10-20Hz and 100-250ms across all 16 subjects at <span
+class="math inline"><em>p</em> &lt; .001</span>uncorrected, using
+Group-optimised MSP. <span id="multi:fig:15"
+label="multi:fig:15"></span></em></figcaption>
+</figure>
+
+## Group MEEG Source Reconstruction with fMRI priors
+
+Finally, in an example of full multi-modal integration, we will use the
+significant clusters in the group fMRI analysis as separate spatial
+priors for the group-optimised source reconstruction of the fused MEG
+and EEG data (see \[Henson et al, 2011\]). Each cluster becomes a
+separate prior, allowing for fact that activity in those clusters may
+occur at different post-stimulus times.
+
+This group-based inversion can be implemented in SPM simply by selecting
+the binary (thresholded) image we created from the group fMRI statistics
+(`fac-scr_fmri_05_cor.nii` in the `BOLD` directory), which contains
+non-zero values for voxels to be included in the clustered priors. This
+is simply an option in the inversion module, so can scripted like this
+(using the same batch file as before, noting that this includes two
+inversions -- MNM and MSP -- hence the two inputs of the same data files
+below):
+
+```matlab
+jobfile = {fullfile(scrpth,'batch_localise_evoked_job.m')};
+tmp = cell(nsub,1);
+for s = 1:nsub
+    tmp{s} = spm_select('FPList',fullfile(outpth,subdir{s},'MEEG'),'^apMcbdspmeeg.*\.mat');
+end
+inputs = cell(4,1);
+inputs{1} = cellstr(strvcat(tmp{:}));
+inputs{2} = {fullfile(outpth,'BOLD','fac-scr_fmri_05cor.nii')};  % Group fMRI priors
+inputs{3} = cellstr(strvcat(tmp{:}));
+inputs{4} = {fullfile(outpth,'BOLD','fac-scr_fmri_05cor.nii')};  % Group fMRI priors
+spm_jobman('serial', jobfile, '', inputs{:});
+```
+
+Note again that once you have run this, the previous "group" inversions
+in the data files will have been overwritten (you could modify the batch
+to add new inversion indices `5` and `6`, so as to compare with previous
+inversions above, but the file will get very big). Note also that we
+have used group-defined fMRI priors, but the scripts can easily be
+modified to define fMRI clusters on each individual subject's 1st-level
+fMRI models, and use subject-specific source priors here.
+
+### Group Statistics on Source Reconstructions
+
+After running the attached script, we will have a new set of
+16$\times$<!-- -->3 GIfTI images for the power between 10-20Hz and
+100-250ms for each subject for each condition after group-inversion
+using fMRI priors, and can put them into the same repeated-measures
+ANOVA that we used above, i.e. the `batch_stats_rmANOVA_job.m` file.
+This can be scripted as (i.e. simply changing the output directories at
+the start from, e.g. `GrpMNMStats` to `fMRIGrpMNMStats`).
+
+```matlab
+srcstatsdir{1} = fullfile(outpth,'MEEG','fMRIGrpMSPStats');
+srcstatsdir{2} = fullfile(outpth,'MEEG','fMRIGrpMNMStats');
+
+jobfile = {fullfile(scrpth,'batch_stats_rmANOVA_job.m')};
+
+for val = 1:length(srcstatsdir)
+    if ~exist(srcstatsdir{val})
+        eval(sprintf('!mkdir %s',srcstatsdir{val}));
+    end
+    
+    inputs  = cell(nsub+1, 1);    
+    inputs{1} = {srcstatsdir{val}};    
+    for s = 1:nsub
+        inputs{s+1,1} = cellstr(strvcat(spm_select('FPList',fullfile(outpth,subdir{s},'MEEG'),...
+            sprintf('^apMcbdspmeeg_run_01_sss_%d.*\.gii$',val))));   
+    end
+    
+    spm_jobman('serial', jobfile, '', inputs{:});
+end
+```
+
+When it has run, press "Results" from the SPM Menu window an select the
+`SPM.mat` file from the `fMRIGrpMSPStats` directory, and choose an
+uncorrected threshold of $p<.001$. You should see results like in
+Figure <a href="#multi:fig:16" data-reference-type="ref"
+data-reference="multi:fig:16">1.16</a>, which you can compare to
+Figure <a href="#multi:fig:15" data-reference-type="ref"
+data-reference="multi:fig:15">1.15</a>. The fMRI priors have improved
+consistency across subjects, even in medial temporal lobe regions, as
+well as increasing significance of more posterior and lateral temporal
+regions (cf., Figure <a href="#multi:fig:11" data-reference-type="ref"
+data-reference="multi:fig:11">1.11</a>, at $p<.001$ uncorrected).
+
+<figure id="multi:fig:16">
+<div class="center">
+<img src="../../../../assets/figures/manual/multi/figure16.png" style="width:150mm" />
+</div>
+<figcaption><em>Group SPM for Faces vs Scrambled power on cortical mesh
+between 10-20Hz and 100-250ms across all 16 subjects at <span
+class="math inline"><em>p</em> &lt; .001</span> uncorrected, using
+Group-optimised MSP and fMRI priors. <span id="multi:fig:16"
+label="multi:fig:16"></span></em></figcaption>
+</figure>
+
+--8<-- "addons/abbreviations.md"