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David,

The two approaches, Beta-series correlation and PPI, are fundamentally different. Beta-series correlations assess the correlation of the estimated trial-to-trial response amplitude. This requires estimating the individual trial response to each trial. In the case of a rapid-event related design the best way to get accurate estimates to to run separate models for each trial (see Mumford et al. 2012). PPI analysis look at how the estimated neural activity during the task is related to activity in other regions. 

If you are going to do a PPI analysis, then I would recommend the gPPI approach as it will deal with all the conditions and phases in your experiment.

Deconvolving BOLD activation in event-related designs for multivoxel pattern classification analyses.

Mumford JA, Turner BO, Ashby FG, Poldrack RA.

Neuroimage. 2012 Feb 1;59(3):2636-43. doi: 10.1016/j.neuroimage.2011.08.076. Epub 2011 Sep 5.


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 Thu, Apr 23, 2015 at 6:10 PM, David <[log in to unmask]> wrote:
Dear all,
in a fast event-related design I defined two seed regions for their significant activity during two different stages of a series of trials (e.g. a preparatory phase and the outcome of a given action).

Now, I was wondering whether I can obtain a measure of functional connectivity for these seeds during the two events of interest.
Since this is a fast-event related design, the two events are separated by ~2.5 sec (with some random jittering).

Am I allowed to run a beta-series correlation between each seed and the rest of the brain during the two relevant phases of each trial?
Should I consider PPI?

Thanks for your help,
Best
D