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Previous studies on event-related functional magnetic resonance imagingexperimental designs are primarily based on linear models, in which a knownshape of the hemodynamic response function (HRF) is assumed. However, the HRFshape is usually uncertain at the design stage. To address this issue, weconsider a nonlinear model to accommodate a wide spectrum of feasible HRFshapes, and propose efficient approaches for obtaining maximin andmaximin-efficient designs. Our approaches involve a reduction in the parameterspace and a search algorithm that helps to efficiently search over a restrictedclass of designs for good designs. The obtained designs are compared withtraditional designs widely used in practice. We also demonstrate the usefulnessof our approaches via a motivating example.

Maximin and maximin-efficient event-related fMRI designs under a nonlinear model