Hi,

On 1 Feb 2008, at 14:14, Yvonne Brehmer wrote:

> Dear experts,
>
> I have more basic questions regarding the practical application of  
> featquery.
>
> In my study I compare 2 age groups at 2 time points (before after  
> training)
> in two memory task conditions (low difficulty vs high difficulty).
>
> I found Time x Group x Condition interactions in the whole –head  
> analysis.
> In order to examine the direction of the effects, I would like to  
> extract
> the parameter estimates to be able to analyze the changes in BOLD  
> activation
> in SPSS and to plot the % signal change.
>
> I read the information about Featquery on the FSL homepage and  
> understand
> the basic steps. However, I still have some questions.
>
> • Which parameters is one actually using for the statistical  
> analysis in
> SPSS and can one just extract them from the featquery output or does  
> one
> need to transform the data somehow?

This is up to you - many different statistical summaries are possible  
in Featquery. If you want the BOLD activation strength then you want  
the PE or COPE values (see the FEAT and Featquery manuals for more on  
these). You can click the right button to tell Featquery to give you  
PE and COPE results in units of % signal change.

> • How is % signal change actually calculated – is that typically  
> averaged
> across voxels in a specific region or does one report the max values  
> and if
> so why?

Featquery gives you several different values for any given input mask/ 
ROI. You can get the mean, the median, the min, max, etc. It's up to  
you to choose which is most appropriate for the question at hand.

> • Is it possible to run the featquery for the higher-level FEAT  
> directory
> (averaged across individuals) and is there a difference if I would  
> run it
> for each individual at a lower level and then average across  
> individuals.

Yes, you can run it at higher-level. You will possibly get different  
answers as some aspects of this whole analysis are nonlinear and so if  
you change the order that you average across voxels you will probably  
get slightly different answers.

> • FSLView also provides one with the option to display % signal  
> change – is
> this actually comparable to the featquery results?

Yes.

> • Can you provide me with a good reference that could illustrate a  
> good
> hands-on example of using featquery to compare groups.

I'm not sure we have an example explicitly written out, but hopefully  
if you read the FEAT amd Featquery manuals carefully it should become  
clear.

Cheers.

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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director,  Oxford University FMRIB Centre

FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 222726  (fax 222717)
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