I am analyzing some task data and have 4 sessions. In one of those
sessions, when I look at the mask that is automatically generated by
SPM in the 1st level analysis, I see some black holes (regions that
are masked out) in several in-brain regions. But... when I look at the
(sw)EPI images that went into the model, they do not seem to be
especially bad. There is a slightly lower signal (compared to the rest
of the brain) in the regions that are masked out, but it's not an
obvious artifact or something.
I might proceed just using the a priori brainmask in MNI space. But..
I am still wondering what the rules/mathematics are for generating the
masks at the 1st level, or how it is calculated?
Johan van der Meer
Netherlands Institute for Neuroscience
Royal Netherlands Academy of Arts and Sciences
Meibergdreef 47, 1105 BA Amsterdam