table of contents
LIPSIA     Conjunction analysis
vnumave
The program 'vnumave' performs a conjunction analysis. Its input are several activation maps. The program can be used in two different modes.
First mode:
For each pixel, 'vnumave' counts the number of input maps whose value in this pixel is above a given threshold.

Example:

vnumave -in zmap_*.v -out result.v -pos 3.0 -type num

In this example, the input images are zmaps of a group of subjects. The resulting image 'result.v' has the same appearance as a zmap. However, the pixel values do not indicate significance values, but simply the number of subjects whose z-values are above the threshold specified in '-pos'. The resulting image can be visualized just like a z-map using standard visualization tools (e.g. 'vlview','v 'vlrender').

Second mode:
For each pixel, 'vnumave' outputs the minimum z-value of all input maps.

Example:

vnumave -in zmap_*.v -out result.v -type zmap

The input images are zmaps of a group of subjects. The output is a zmap that corresponds to a logical 'AND' of all input images (see reference below).


Parameters of 'vnumave':
-help
Prints usage information.
-in
Input file. Default: (none)
-out
Output file. Default: (none)
-pos
Positive threshold for individual zmaps. Default: 3.0
-neg
Negative threshold for individual zmaps. Default: -10000.0
-type [ num | zmap ]
Type of output. Default: num
Literature:

T.Nichols,M.Brett,J.Anderson,T.Wager,J.B. Poline (2004). "Valid conjunction inference with the minimum statistic." NeuroImage, 25, 653-660.



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.