Alexandre,

Please see the inline comments below.

On Tue, Dec 10, 2013 at 4:30 AM, Alexandre Obert <[log in to unmask]> wrote:

Dear all,

I would like to have your opinion about analyses I would like to perform.
I have two experimental conditions : cond1 and cond2 and a fixation cross.

Because you have 3 different conditions (c1, c2, and fixation), you should use the gPPI toolbox, rather than the PPI functions in SPM. gPPI has been shown to be more accurate at estimating the PPI effects than the PPI function in SPM (see Cisler et al. 2013 and McLaren et al. 2012).

I performed 1st level for each of my participants and set two kind of contrasts : cond1>cross and cond2>cross.
Then, theses contrasts were enter in a 2nd level analyses trough a paired t-test (inclusively masked by the effect of cond1).
I observed the activation of a parietal area. I wonder whether this region is linked to timecourse of other regions in this paired t-test contrast.

My first idea was to perform a PPI analysis on each of my participants using a VOI set to the coordinate of this parietal area but I'm not entirely confident about this...
A reason about this hesitation concern the use of this activation to set the VOI become from an article of Spotorno et al. (2012) : "For a PPI analysis to be optimal, however, it is important to ensure that the activity in the seed region is not correlated with the contrast of interest. In our case, none of the seed regions that would be used in the PPI analyses should be activated in the Ironic>Literal contrast".
I think it's quite similar to the analysis I would like to perform.

This is effectively saying that if condition 1 is different than condition 2, then you can't test if the connectivity is different by condition using the region as a seed. I think this dates back to the PPI models in SPM where cond1-cond2 is entered as an HRF regressor and as a PPI regressor. The poor model may have hindered detection of real results. gPPI has been shown to more sensitive to detecting true differences and a reduction in false positives.

But I in other posts, I saw that : "They don't need to be independent of the main result. When you do a PPI analyses, it is a separate and completely different analyses from that of the task activation. Thus, using the task results to select your seeds is not double-dipping. "

I'm a little confused about the kind of analysis I should perform and about the relevant VOI...

If you clearly state your research question, I don't think you will have an issue. For example, In the region that is differentially responsive to c1 and c2, does the connectivity with this area also change for c1 and c2.

There are two aspects of neural function: (1) the neural response in each area (relative activation and deactivation); and (2) connectivity between areas. These are separate questions and can have different answers or similar answers.

Any advice ?

Regards,

Alexandre Obert