I'm not Steve, but I might be able to help. The featquery webpage says:
"If you select Convert PE/COPE values to %, any PE or COPE parameter
estimate or contrast values will be converted to percentage signal change
values before reporting. This is achieved by scaling the PE or COPE values
by (100*) the peak-peak height of the regressor (or effective regressor in
the case of COPEs) and then by dividing by mean_func (the mean over time of
filtered_func_data)."
Instead of figuring out PPheights and mean_func for your ROI, you can
estimate that scaling factor and apply it to your varcope values.
1) Extract cope & varcope WITHOUT clicking "Convert PE/COPE values to %"
2) Extract cope_psc WITH clicking "Convert PE/COPE values to %"
3) varcope_psc = varcope * (cope_psc / cope)
What I'd like to know is: is this just an estimate, or is this actually
precise (assuming that you use the same peaks, masks, etc.)???
Thanks,
--Greg
____________________________________________________________________
Greg Burgess, Ph.D.
Research Associate, Institute of Cognitive Science
University of Colorado - Boulder
Phone: 303-735-5802
Email: [log in to unmask]
University of Colorado - Boulder
UCB 594
Boulder, CO 80309-0594
On Tue, 26 Feb 2008 09:08:09 +0000, Yvonne Brehmer <[log in to unmask]> wrote:
>Hi Steve,
>
>I checked your recent replies to the questions regarding error bars in %
>signal change.
>
>One easy way is to get the COPE values with and without the '%' conversion,
>and then apply that factor to the square root of the varcope.
>
>Even though you might see this as a pure repetition, I would very much
>appreciate if you could be more explicit in how to do this maybe including
>the syntax code to run the calculation in fslmaths if possible.
>
>Thanks for your help,
>Yvonne
>========================================================================
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