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Hi Doug, I am referring to deconvolution in the SPM sense, where they use (something like) ridge regression to get an estimate of neuronal activity from the measured BOLD response. The idea is to use that neural time series to construct predictors for a psycho-physiological interaction (PPI) analysis, as in Gitelman et al. 2003 ( https://cfn.upenn.edu/stslab/wiki_links/fmri_club/fxncxn/Gitelman_etal_2003_..., see page 201).
Thanks! Caspar
Am Mo., 12. Aug. 2019 um 16:02 Uhr schrieb Greve, Douglas N.,Ph.D. < DGREVE@mgh.harvard.edu>:
When you say deconvolution, what do you mean exactly? There is an FIR model (finite impulse response) that will extract the hemodynamic response without any assumptions, ie, the signal average at stimulus onset, the signal average at 1TR post onset, the signal average at 2TR post onset, etc.
On 8/9/2019 7:10 AM, Caspar M. Schwiedrzik wrote:
External Email - Use CautionHi! I was wondering whether it is possible to do deconvolution of an fMRI time series with FSFAST? Specifically, I would like to get a deconvolved signal from a region of interest to prepare predictors for a PPI analysis. Additional considerations: data is from an event-related design, and was acquired with MION contrast agent. I found some older documentation on selxavg2, but I am not sure whether that still applies (I am using version 5.3). Also, I do not need an event-related average as output, but a continuous time series.
Thanks for any advice! Caspar
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