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Dear Alex, >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 >the second-half): >EV1 EV2 >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. Joe -------------------- 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]