table of contents
LIPSIA     Multiple comparison correction using single thresholding
valphasim
This program performs multiple comparison correction using a combination of individual voxel probability thresholding and minimum cluster-size thresholding. The probability threshold is supplied by the user, the cluster-size threshold is computed by this program using Monte-Carlo simulations.

Example:

valphasim -in zmap.v -z 2.576 -fwhm 8.0 -report list.txt -out test.v

This command calculates the minimum cluster-size threshold and corresponding p-values given the original significance threshold of z=2.576 (uncorrected). The input image 'zmap.v' serves as a mask for the Monte-Carlo simulations. It should therefore have the same geometrical properties as the actual zmap to be analyzed, i.e. the same voxel size, spatial extent, etc. The Monte-Carlo simulation fills the space of non-zero voxels in this zmap-mask with randomly generated p-values and counts the number of false positives.

Spatial smoothness

The parameter '-fwhm' should correspond to the spatial smoothness of the data. This value depends both on the size of the spatial filter used when preprocessing the data plus the intrinsic smoothness of the data prior to spatial filtering. In 'vcolorglm' and 'v2ndlevel', and all second-level programs this value is automatically estimated, and written into the header of the zmap. It can be read using the command:

> grep -a smoothness zmap.v

Note, that there no smoothness estimation implemented in 'vwhiteglm'. Please use 'vcolorglm' to perform a smoothness estimation.

Note further, that the smoothness estimation should always be counter-checked by visual comparison with the output image generated by 'valphasim'. The output image represents one of the randomly generated test images. It can be visualized as if it were a zmap using 'vlv' oder 'vlview'. It can be used to assess whether the 'fwhm'-parameter reflects the spatial smoothness of the data.
Example
The output of 'valphasim' is a table of corrected p-values and minimum cluster sizes:

Example output:

fwhm: 5.00mm, seed: 555, numiter: 1000
z: 2.57600, p: 0.00500
image dims: 80 100 80
num voxels: 109429
voxel size: 2.00 x 2.00 x 2.00 = 8.00 mm^3

  mm^3     freq   maxfreq   corrected p
8.00    10163 0 1.00000
16.00    6843 0 1.00000
24.00    4881 0 1.00000
32.00    4152 0 1.00000
40.00    3121 0 1.00000
...
832.00    3 2 0.05500
840.00    1 1 0.05300
848.00    2 2 0.05200
856.00    2 2 0.05000
872.00    1 1 0.04800
880.00    1 1 0.04700

From this table, the minimum cluster size has to be determined which is associated to the largest p-value < 0.05. In our example, this is 0.048, and the minimum cluster size is 872 mm^3. This result can be applied to the data using 'vpretty' and 'vblobsize' in the following way:

vpretty -in zmap.v -out correct_zmap.v -pos 2.576 -minsize 872

vblobsize -in zmap.v -out correct_blob.v -pos 2.576 -minsize 872 -system talairach

The colums 2 and 3 of the above table provide the frequency with which a cluster size has been detected or was found to be the largest cluster size within the Monte-Carlo simulations, respectively.

Remark: 'valphasim' is based on the publications cited below.

Parameters of 'valphasim':
-help
Prints usage information.
-in
Input file. Default: (none)
-out
Output test image. Default: (none)
-z
z threshold. Default: 2.576
-fwhm
fwhm of spatial smoothness in mm. Default: 5
-seed
Seed value for random number generator. Default: 555
-iter
Number of iterations. Default: 1000
-report
Output report file. cluster and p-value list in ASCII.
Literature
S.D. Forman, J.D. Cohen, M. Fitzgerald, W.F.Eddy, M.A. Mintun, D.C. Noll. Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. MRM 33:636-647 (1995).

J. Xiong, J.-H. Goa, J.L. Lancaster, P.T. Fox. Clustered Pixels Analysis for Functional MRI Activation Studies of the Human Brain. Human Brain Mapping 3:287-301 (1995).



Max Planck Institute for Human Cognitive and Brain Sciences. Further Information: lipsia@cbs.mpg.de
Copyright © 2007 Max Planck Institute for Human Cognitive and Brain Sciences. All rights reserved.