Hello,
 
I’m a graduate student with experience running task GLM
analyses, but my lab is now interested in performing gPPI analyses on fMRI data
collected during a visual encoding task. 
We are interested in whether the connectivity of our regions of interest
during encoding is modulated by subsequent memory (hit or miss during retrieval).  During retrieval (out of scanner), participants
also indicate their confidence in their decision (high confidence / low
confidence). 
 
Therefore we have three task conditions  (Subsequent Hit-High Confidence [Hit-HC],
Subsequent Hit-Low Confidence [Hit-LC], Subsequent Miss), with implicit baseline
as a fourth condition (per [url=https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1312&L=spm&D=0&1=spm&9=A&J=on&d=No+Match%3BMatch%3BMatches&z=4&P=414240)]listserv[/url]
post).  Our task GLM also includes
temporal derivatives of the three task conditions, as well as six motion
parameters and regressors for motion outliers.
 
I have a few questions about gPPI:

• My understanding of PPI
  involves change in coupling across task conditions relative to the baseline
  (see footnote A).  However, can this approach
  be used to investigate modulation of connectivity between task (i.e. encoding)
  and baseline?  The gPPI script creates
  contrasts for ‘none minus Hit-HC’, ‘Hit-HC minus none’, etc.  Can the results of these contrasts be
  reasonably interpreted as voxels where coupling with the seed region is
  modulated between Hit-HC and implicit baseline? This
  post would seem to indicate it can, but then what are the task and baseline
  connectivity relative to? If it's relative to the other two task conditions
  (Hit-LC and Miss), is it correct to assume that a general encoding (Hit-HC +
  Hit-LC + Miss) compared to baseline is not a possibility?
• Visual stimuli are
  presented for four seconds each – are there arguments to be made for modeling
  the stimuli as events, or giving them their 4s durations? This [url=https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1612&L=SPM&P=R924&1=SPM&9=A&J=on&d=No+Match%3BMatch%3BMatches&z=4]answer[/url]
  seems to suggest we should give the 4s duration, but the linked website
  primarily focuses on the need to give the duration when it’s variable (which
  ours isn’t).
• Related to #2, if we do
  give the duration of 4s, should this be done for both the individual
  first-level analysis and the PPI?
• As noted above, our task
  GLM includes temporal derivatives for each of the three task conditions, which
  the gPPI toolbox also includes in the PPI GLM. 
  I’m only creating interaction regressors for the three task conditions
  and not the temporal derivatives – does the inclusion of the temporal
  derivatives in the GLM complicate interpretation of the gPPI results? ([url=https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1304&L=SPM&P=R74001&1=SPM&9=A&J=on&d=No+Match%3BMatch%3BMatches&z=4]Answer[/url])
• Building on #4, when
  adjusting for the ‘effects of interest’ F-contrast, should that contrast
  include the temporal derivative regressors or only the three task regressors?

 
I’m happy to provide additional detail where helpful.  Thank you!
 
A) “Also note that PPI effects
(interaction terms in PPI model) are always relative to the baseline state (the
baseline state is defined by the zero values of the interaction term), so they
provide a relative measure of connectivity characterizing differential
task-specific effects, rather than an absolute measure of connectivity such as
that estimated using standard functional connectivity analyses (e.g. weighted
correlation measures).” (CONN toolbox manual)