Hi SPMers,
We are doing a rapid event related study. There are initially four
types of trials. These are then modified on a subject by subject
basis by subsequent memory effects. This leaves us with 8 trial
types with vectors of onsets that differ for each subject and each
session. We initially used the stochastic design feature to make a
model of the four initial trial types. We also included fixation
trials which we did NOT explicitly model thereby giving us some
"jitter". The ITI is 3 seconds. The TR is 1.5 seconds. Our results
have been disappointing. I have two questions:
1) should we explicitly model the fixation trials? i.e. give them a
column in the design matrix. And if we don't, should we say yes to
the variable durations question?
2) high pass and low pass filtering:
a) the defaults for the high pass filter are different for different
subjects and different sessions. This is no doubt because of the
different actual onsets (based on the different subsequent memory).
But should we change them so that they are all the same?
b) We have been using gaussian-4sec for low pass filtering. When we
redid our analysis without any low pass filtering we get much more
robust activations for some contrasts and quite different activations
for other contrasts. What is going on here? and what is appropriate
for us to use? If we use a 4 sec filter and our ITI is 3 seconds are
we filtering out our signal rather than the noise?
Thanks very much for your input on this.
Alex Golby
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