As long as the regressors aren't correlated, you will be fine.
However, there are a few things to consider in your PPI analysis:
(1) the duration of your events. if your duration is 0, then PPI only
uses the 1st bin of the upsampled data, typically 1/16 of a TR.
(2) if you have any fixation time (since you have at least
2conditions), then you should look into using gPPI. In general,
anytime that there are more than 2 cognitive states (task and fixation
both count), you should use gPPI.
(3) It appears that you would at least ~10 events per run to do PPI.
Fewer trials will increase the collinearity.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Wed, Sep 5, 2012 at 12:40 AM, Daehyun Jung <[log in to unmask]> wrote:
> Dear SPMers,
>
> I have some questions concerning PPI analysis.
>
> I tried to find the brain area correlating with TPJ, modulated by the psychological variable (other vs. self)
>
> I used the other-self contrast in "spm.mat" to extract the VOI.
>
> Then, I used the same SPM file to generate the PPI variables accroding to other-self contrast weight.
>
> The point is ...
>
> Is it ok to use the same contrast weight from the same "spm.mat" file during both extraction of VOI
>
> and generation of PPI variable?
>
>
> Actually, I have done the analysis already.
>
> And I checked the colinearty between PPI-interaction regressor (column 1) and
>
> Psychological variable regressor (column 3) from the design orthogonality menu in SPM8.
>
> I can not find any colinearity for each participant.
>
> However, I might be worried about the concept of PPI analysis.
>
> So, Could you please tell me whether the analysis I have done so far is correct or not?
>
>
>
>
>
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