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The analysis of brain activations using functional magnetic resonance imaging (fMRI) is an active area of neuropsychological re- search. Standard techniques for analysis have traditionally focused on nding the most signicant areas of brain activation, and have only re- cently begun to explore the importance of their spatial characteristics. We compare fMRI contrast images and signicance maps to training sets of similar maps using the spatial distribution of activation values. We demonstrate that a Fisher linear discriminant (FLD) classier for either type of map can dierentiate patients from controls accurately for Alzheimer's disease, schizophrenia, and mild traumatic brain injury (MTBI).