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Using FSL - Contrasts, Thresholding, Rendering

If you are not carrying out a Full analysis and are re-running Post-stats, a button appears to allow you to Edit contrasts. This allows setup of contrasts and F-tests, to be run on the previous analysis.

If you choose a mask for Pre-threshold masking then all stats images will be masked by the chosen mask before thresholding. There are two reasons why you might want to do this. The first is that you might want to constrain your search for activation to a particular area. The second is that in doing so, you are reducing the number of voxels tested and therefore will make any multiple-comparison-correction in the thresholding less stringent. The mask image chosen does not have to be a binary mask - for example, it can be a thresholded stats image from a previous analysis (in the same space as the data to be analysed here); only voxels containing zero in the mask image will get zeroed in this masking process. If pre-threshold masking is used, it is still necessary to carry out thresholding.

Thresholding: After carrying out the initial statistical test, the resulting Z statistic image is then normally thresholded to show which voxels or clusters of voxels are activated at a particular significance level.

If Cluster thresholding is selected, a Z statistic threshold is used to define contiguous clusters. Then each cluster's estimated significance level (from GRF-theory) is compared with the cluster probability threshold. Significant clusters are then used to mask the original Z statistic image for later production of colour blobs. This method of thresholding is an alternative to Voxel-based correction, and is normally more sensitive to activation. You may well want to increase the cluster creation Z threshold if you have high levels of activation.

The FEAT web page report includes a table of cluster details, viewed by clicking on the relevant colour-overlay image. Note that cluster p-values are not given for contrasts where post-threshold contrast masking (see below) is applied, as there is not a sensible p-value associated with the new clusters formed after masking.

If Voxel thresholding is selected, GRF-theory-based maximum height thresholding is carried out, with thresholding at the level set, using one-tailed testing. This test is less overly-conservative than Bonferroni correction.

You can also choose to simply threshold the uncorrected Z statistic values, or apply no thresholding at all.

Contrast masking: You can setup the masking of contrasts by other contrasts; after thresholding of all contrasts has taken place you can further threshold a given Z statistic image by masking it with non-zeroed voxels from other contrasts.

This means that of the voxels which passed thresholding in the contrast (or F-test) of interest, only those which also survived thresholding in the other contrasts (or F-tests) are kept.

As a further option, the generated masks can be derived from all positive Z statistic voxels in the mask contrasts rather than all voxels that survived thresholding.

Rendering: The Z statistic range selected for rendering is automatically calculated by default, to run from red (minimum Z statistic after thresholding) to yellow (maximum Z statistic). If more than one colour rendered image is to be produced (i.e., when multiple constrasts are created) then the overall range of Z values is automatically found from all of the Z statistic images, for consistent Z statistic colour-coding.

If multiple analyses are to be carried out separately, Use preset Z min/max should be chosen, and the min/max values set by hand. Again, this ensures consistency of Z statistic colour-coding - if several experiments are to be reported side-by-side, colours will refer to the same Z statistic values in each picture. When using this option, you should choose a conservatively wide range for the min and max (e.g., min=1, max=15), to make sure that you do not carry out unintentional thresholding via colour rendering.

With Solid colours you don't see any sign of the background images within the colour blobs; with Transparent colours you will see through the colour blobs to the background intensity.

If you are running a Higher-level analysis you can select what image will be used as the background image for the activation colour overlays. The default of Mean highres is probably the best for relating activation to underlying structure. For a sharper underlying image, (but one which is not so representative of the group of subjects), you can instead choose to use the highres image from the first selected subject. You can alternatively choose to use the original lowres functional data for the overlays, or the standard-space template image.