BrainVoyager version: 22.4.4
Dataset used: Getting Started Guide data
Using masks during either single or multi-subject GLM analysis, one can effectively influence the analysis e.g. either to exclude brain regions of no interest from the analysis (to reduce the multiple comparisons problem) or also to mask contrasts with each other.
This Single Study GLM example shows how to restrict the analysis using a mask and how you can visually and numerically (number of voxels used) check the difference. If you want to know how to create a mask file, please check out the Creating Mask section.
Mask Specification in the Single Study General Linear Model Dialog
To test the spatial restriction of the anlysis by exploiting a mask, we load the original (MNI) VMR, link a VTC and open the Single-Study GLM dialog.
You can invoke the "Single Study GLM Options" by clicking on the button “Options” in the GLM dialog. In the "Mask-based (e.g. cortex-based) analysis field" of the “Masking functions” tab you can choose to load a mask file (*.msk) or a VOI file (*.voi) to restrict the number of voxels in your analysis. In the current example we load a grey matter mask file.
GLM Result
The GLM result should not contain any activations within the white matter or the skull. We could reduce the minimum threshold massively to check the maximum extent of the statistical map and make sure that only grey matter regions have been included in the analysis. We can also check out the number of voxels used in the current GLM in the “Overlay GLM“ dialog.
To compare the masked analysis to the original result using the full dataset, we run the GLM without masking.
We check the number of included voxels again.