>Assuming this is OK and I have only these 2 EVs, I assume the following
>contrasts would represent (take EV1 as the first-half regressor & EV2 as
>1 0 I>N for first half only
>0 1 I>N for second half only
>1 1 I>N for the entire task
Your design looks fine assuming that the box-car is modeling the
interference condition and that the neutral condition is left as an
implicit baseline. The one thing I would add is to guarantee that the main
effect of I>N is not being driven solely by either the first or second
half, you'd need to do some form of inclusive masking -- that is, mask [1
1] with [1 0] and [0 1] at some arbitrary threshold. BTW, it's probably
best to use a voxel threshold rather than a cluster threshold for this.
Then [1 -1] would yield I trials with more activation in the first half
than second (it would not include N trials).
>Finally, is the choice of HRF convolution merely one of preference?
>Are their optimal convolutions for particular designs?
>Does it matter in a boxcar design?
Yes, the HRF choice is arbitrary unless you have some reason to choose
specific parameters (time-to-peak, dispersion, etc). The optimal
convolution will depend on the subject and brain region and probably can
not be known a priori. So you could you a less constrained basis set but
then you end up using F-tests and potentially over-fitting. There are two
recent papers in NeuroImage by Woolrich et al and Handwerker et al relevant
to this. And yes, it does still matter with box-car designs but much less
than in event-related designs.
Hope this helps.
Joseph T. Devlin, Ph. D.
FMRIB Centre, Dept. of Clinical Neurology
University of Oxford
John Radcliffe Hospital
Headley Way, Headington
Oxford OX3 9DU
Phone: 01865 222 738
Email: [log in to unmask]