Hello Dianne,
I feel moved to expand slightly upon the answer provided by my esteemed
colleague Dr. Weissman. (hi Daniel!!) Modelling bad scans with a
single vector
containing ones for the bad scans will remove variance rougly associated with
the average of those bad scans. Any variance between the bad scans
will not be
removed. I imagine that for many types of bad volumes (such as
excessive bursts
of noise, or from scanner artifacts from bad k-space datapoints), this
will not
be sufficient.
To completely remove the influence of every bad scan from your model, you will
have to input a separate column for _each_ bad scan containing all zeros and
one non-zero value (at the location of that bad scan).
Ken
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Ken Roberts
Woldorff Laboratory
Center for Cognitive Neuroscience, Duke University
(919) 668-1334
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