When you do VBM analysis, you see many files are generated in your stats directory. Suppose you are doing a two sample t-test. You see files like below.
- beta_0001
- beta_0002
- con_0001
- mask
- ResMS
- RPV
- spmT_001
Ged Ridgway made a clear explanation of these files in NITRC discussion forum. http://www.nitrc.org/forum/message.php?msg_id=6483
It is important to know what these files are, so I quote his post with some modification.
- beta
- con
- mask
- ResMS
- RPV
- spmT
The estimated linear model parameters at each voxel. In a two-sample design, these are just the two group mean images. beta_0001 is a mean image of group A, and beta_0002 is a mean image of group B.
The contrasts of the parameters. If one makes a contrast of [-1 1], the con_0001 will simply be beta_0002 – beta_0001
A binary image indicating which voxels were considered in the analysis. If this mask is too small, you may miss the region you are interested in. If too big, it is less likely to survive multiple comparison. So it is worth checking the mask image before you draw some conclusion from your analysis.
The estimated variance (residual mean squares), from which the above-mentioned standard error is derived.
In more detail, the standard error is proportional to the square root of ResMS and a term that relates to the design matrix X and contrast c as sqrt(c’*pinv(X’*X)*c), which (in two sample t-test) roughly reflects the fact that the standard error is inversely proportional to the number of subjects one has.
The resels-per-voxel image related to the smoothness (roughness)
estimate needed for random field theory.
The t-statistic maps formed by dividing the contrast image by its estimated standard error.
