Detecting activations in event-related fMRI using analysis of variance

The most common design of a functional MRI (fMRI) experiment is a block des ign. The use of rapid imaging, however, and carefully designed paradigms ma kes the separation of cognitive events possible. Such experiments make use of event-related paradigms, in which a task involving several cognitive pro cesses is repeated. In analyzing data from such experiments, existing metho ds often prove inadequate, because the prediction of the exact shape or tim ing of the time course is difficult. Here we present an analysis of varianc e (ANOVA) method for analyzing fMRI data that does not require any assumpti ons about the shape of the activation time course. Consequently, this metho d can simultaneously detect brain areas showing a variety of stimulus-locke d time courses in the same experiment. The utility of this technique is dem onstrated by the analysis of data from two event-related paradigms in which regions of activation are detected that correspond to a variety of distinc t neural processes, yielding significantly different temporal signal change s. (C) 1999 Wiley-Liss, Inc.