Hi,
I am analysing a word reading/recognition task which was run in a blocked
design (20 s on, 20 s rest). That is fine and simple.
Within each 20 s on period, there are 10 words presented (1 every 2
seconds), half are previously presented words and half are new words. I want
to use an event-related analysis to find the difference between new words
and previously presented words. This is essentially a stochastic design
(since words are presented in random order) with SOAmin of 2 seconds which,
according to Friston et al (1999, NeuroImage 10:607-619), should have high
efficiency for analysing the differential response.
But I have 24 slices with TR=2.88s (120 ms per slice) so there is a 2.76s
delay between acquisition of the first and last slice. I can not use the
slice timing correction in this case because the frequency of BOLD changes I
want to model is much higher than 1/{2TR} (according to the abstract of
Henson et al, HBM1999, NeuroImage 9(2):S125).
If I include temporal derivatives with the canonical HRF to compensate for
this delay between slices, is this an appropriate method? If so, how do I
specify contrasts? Does anyone have any other suggestions?
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