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There is no problem in theory for concatenating the runs. However, there are practical concerns: (1) baseline shifts between runs (constant regressor per run) (2) estimates of neural activity need to be within each run and not cross over between runs (3) Filtering should be done on a per run basis (4) AR(1) computations should be done on a per run basis as well #2-4 are not easily done, but the next release of the gPPI toolbox will have a concatenation option. 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 ===================== This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is intended only for the use of the individual or entity named above. If the reader of the e-mail is not the intended recipient or the employee or agent responsible for delivering it to the intended recipient, you are hereby notified that you are in possession of confidential and privileged information. Any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited and may be unlawful. If you have received this e-mail unintentionally, please immediately notify the sender via telephone at (773) 406-2464 or email. On Thu, Sep 26, 2013 at 10:35 AM, Chris McNorgan <[log in to unmask]>wrote: > Hello SPM users, > > I was wondering if I could tap in to your collective wisdom: > A colleague wishes to use PPI in SPM8 to explore a straightforward > contrast [A vs NOT_A] on some data acquired over 10 runs. She has been > following along with the SPM8 manual (Chapter 33), where it suggests > concatenating the runs into a single super-session. When she does so, and > performs a GLM on the concatenated super-session, she notes that the A vs > NOT_A effects are noticeably diminished (compared to when 10 individual > runs are entered into the GLM analysis), and is naturally concerned that > this will adversely impact the sensitivity of the PPI analysis. I assume > the apparent reduction in the magnitude of the observed effects are related > to mathematical quirks (e.g., things like degrees of freedom) and an > increased intra-session variability (all the between-session fluctuations > now appear within the super-session). > > Given that the PPI analysis can include block regressors, is this a cause > for concern? If so, what is the appropriate course of action? > > Thanks >