Dear Matthew,
In the last 2 days we also tested our data in FSL v6.00 (with the same options; i.e. outlier de-weighting) and the analysis ran without error, and there were no missing slices in the final zstat1 images.
We compared zstat1 between FSL 6.0.1 and FSL v6.00 and the values were exactly the same in the voxels of slices that were not missing in FSL 6.0.1 analysis. As you suggested, we inspected our first-level filtered_func_data and the registrations for all of our subjects, but we didn't realized anything obviously wrong. We also compared varcope1 between the two FSL versions and the values were exactly the same in the slices calculated by FSL 6.0.1 as well. We checked varcope1, prob_outlier1 (each volume) and global_prob_outlier1 generated by FSL v6.00, but no weard data were detected in the slices which were missing in version FSL 6.0.1.
Based on the above we think that the problem is related to the FSL 6.0.1 rather than our raw data. Do you have any idea how to move forward? Should we downgrade our FSL version or solve the problem another way?
Best,
Gábor
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