Dear all,

I am running into a strange problem while running second-level GLM (using SPM12) of multi-session fMRI from first-level. I am getting the following error –

```
Error using betainc
X must be in the interval [0,1].
Error in spm_Tcdf (line 109)
F(Q) = xQxPos -(xQxPos*2-1).*0.5.*betainc(v(Qv)./(v(Qv)+x(Qx).^2),v(Qv)/2,1/2);
Error in spm_ECdensity (line 38)
EC(1,:) = 1 - spm_Tcdf(t,v);
Error in spm_P_RF (line 63)
EC = spm_ECdensity(STAT,Z,df);
Error in spm_uc_RF (line 37)
[P, P, p] = spm_P_RF(1,0,u,df,STAT,R,n);
Error in spm_uc (line 31)
u = spm_uc_RF(a,df,STAT,R,n);
Error in spm_getSPM (line 790)
uu = spm_uc(0.05,df,STAT,R,n,S);
Error in spm_results_ui (line 261)
[SPM,xSPM] = spm_getSPM;
Error while evaluating UIControl Callback.
```

This error pops up for both script and GUI.

I have attached the deisgn_matrix image below…

I have no issues in computing the contrasts in the first-level. I am attaching the snippet of the script I used to compute the first-level contrast…

```
%---------------------
% 4. Compute contrasts
%---------------------
% Double check which regressors are in which columns
cd(model_path);
load('SPM.mat');
colnames = SPM.xX.name';
disp('Design matrix columns are:')
disp(colnames)
% Read in the contrast table
c_path = 'E:\Simba\Contrast_table_GLM_pmod4.xlsx'
t = readtable(c_path);
cnames = t.Var1; % contrast names
cvecs = table2array(t(:,2:end)); % contrast matrix
ncon = numel(cnames); % number of contrasts
% Create a batch
matlabbatch = {};
matlabbatch{1}.spm.stats.con.spmmat= {spmMatPath};
for j = 1:ncon
matlabbatch{1}.spm.stats.con.consess{j}.tcon.name = cnames{j};
matlabbatch{1}.spm.stats.con.consess{j}.tcon.weights = cvecs(j,:);
matlabbatch{1}.spm.stats.con.consess{j}.tcon.sessrep = 'none';
end
% Loop over contrasts
matlabbatch{1}.spm.stats.con.delete = 0;
matlabbatch{1}.spm.stats.con.spmmat = {spmMatPath};
```

The same second-level script works perfectly for single-session contrasts…

Any help would be hugely appreciated…

Thank you…

EDIT : This is solved! It was due to SPM not being able to compute the t statistic due to low sample size at the 2nd level.