Methods for analysing functional imaging data have evolved rapidly over the last ten years. Standardized techniques based on formal mathematical and statistical theory and rigorous empirical validation have been proposed to facilitate comparisons of biological results between laboratories. This paper examines an image analysis technique that appears to identify unexpectedly large numbers of activated brain areas for the data collected. It concludes that the method may not adequately control for false positives, rendering interpretation of the functional anatomy difficult.