[caret-users] Threshold & cluster size

John Harwell john at brainvis.wustl.edu
Fri Jun 15 09:23:39 CDT 2007

Hi Katja,

The thresholds only display values greater than the threshold value.   
So you could use the metric math dialog (Attributes Menu->Metric- 
 >Mathematical Operations to convert your p-values to (1 - p) values  
(I may have seen this called "Q") and then set the threshold to  
0.999.  On the Metric Math Dialog, set both Column A and Result to  
your metric data.  Check the button next to Multiply Column A by  
Scalar, enter -1.0 for the value, and press the Apply button.  Next,  
check the button next to Add Scalar to Column A, enter 1.0 for the  
value, and press the Apply button.

To find clusters use Attributes Menu->Metric->Clustering and  
Smoothing.  Press the Help button and it will describe how to use the  
clustering option.  You can also use the threshold values for the  
clusters to find only nodes with values less than 0.001.

John Harwell
john at brainvis.wustl.edu

Department of Anatomy and Neurobiology
Washington University School of Medicine
660 S. Euclid Ave.    Box 8108
St. Louis, MO 63110   USA

On Jun 15, 2007, at 9:04 AM, Katja Umla-Runge wrote:

> Hello everyone,
> I'm a new Caret user and am currently trying to display t-contrast  
> fMRI images (SPM99) in Caret. What kind of threshold does Caret  
> require (Display control --> metric --> threshold Pos)? I performed  
> uncorrected t-tests in SPM with p < .001. Is 0,001 the value to  
> insert? And how would you let Caret know that a threshold refers to  
> correction for multiple comparisons? If you only want those voxels  
> displayed that exceed a given cluster size (e.g. minimal cluster  
> size = 20 adjacent voxels), how would you go about?
> Thank you for your help
> Katja
> -- 
> Dipl.Psych. Katja Umla-Runge
> Saarland University
> Department of Psychology        phone: +49 - (0)681 - 302 4643
> P.O.Box 151150                  fax:   +49 - (0)681 - 302 4049
> D-66041 Saarbruecken            email: k.umla-runge at mx.uni-saarland.de
> www.BrainCog.de
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