I'm trying to implement a first-level GLM with EVs representing
condition (two levels,negative affect and neutral), activity within a
specific region over that time series (say, avg. amygdala activity), and
their interaction. My main interest is in the interaction effect as a
representation of connectivity between the specific region (amygdala)
and the rest of the brain, as a function of negative affect (what I
believe is often referred to as an analysis of "psychophysiological
interactions"). I haven't seen anything on this listserv or in the FSL
documentation on how specifically to carry this out via FEAT (let me
know if I've missed anything). But I imagine I could carry it out by
extracting post-processed intensity values within the amygdala, dumping
this to a text file and adding it as a column in the design matrix to be
run on that same time series. I could then add an EV for my task to the
same design matrix, and use the GUI option to multiply them together for
the interaction. My questions are:
1) Does this approach seem valid?
2) Do I need to worry about the different heights of the EVs
representing my task (e.g., 0 to 1) and the amygdala activity (e.g., 0
to the max. intensity value, in the thousands)? Specifically, I'm
concerned with the interpretability of the EVs if I enter them into a
higher level analysis examining the interaction within and across groups
(e.g. higher-level analyses), as well as contrasting interactions within
and across subjects. If height is an issue here, can you suggest a
correction I could apply to the amygdala EV before entering it into the
analysis that might take care of this?
Thanks,
John Herrington
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