> In an event-related design like this, I would have thought that you SHOULD
> model the 'fixation' events explicitly. If they are not modelled, then
you
> are asking of each voxel the question 'can a significant amount of the
> variance be explained by the modelled covariate for event A' (with a
> contrast 1 0 0), whereas I would rather model them explicitly and then ask
> the question 'is significantly more variance explained by the modelled
> covariate for event A than for the modelled covariate for event D' (with a
> contrast 1 0 0 -1). I am assuming, though, that D is an actual event
(such
> as the appearance of a fixation point or some other temporal cue) rather
> than just an arbitrarily chosen moment between the real events.
In our normal usage of the term "null events", we refer to imaginary
events that are, in fact, no different from the interstimulus baseline
(ie completely undetectable by subjects). If you like, they are used
simply to achieve a particular random distribution of times between
stimuli (ISIs). I think this is consistent with the original use of
"fixation" trials by Dale & Buckner (1997) - though someone please
correct me if I'm wrong!
If you do include "fixation trials" that are different from baseline
(as in Richard's example, the presentation of a fixation cross against
an otherwise blank screen) then Richard is exactly right that they
should be modelled. This potential confusion may be why "null event"
is perhaps more suitable than "fixation trial".
Rik
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Wellcome Department of
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