Abstract
The term "mapping" in the context of brain imaging conveys to most the concept of localization; that is, a brain map is meant to reveal a relationship between some condition or parameter and specific sites within the brain. However, in reality, conventional voxel-based maps of brain function, or for that matter of brain structure, are generally constructed using analyses that yield no basis for inferences regarding the spatial nonuniformity of the effects. In the normal analysis path for functional images, for example, there is nowhere a statistical comparison of the observed effect in any voxel relative to that in any other voxel. Under these circumstances, strictly speaking, the presence of significant activation serves as a legitimate basis only for inferences about the brain as a unit. In their discussion of results, investigators rarely are content to confirm the brain's role, and instead generally prefer to interpret the spatial patterns they have observed. Since "pattern" implies nonuniform effects over the map, this is equivalent to interpreting results without bothering to test their significance, a practice most of the experimentally-trained would eschew in other contexts. In this review, we appeal to investigators to adopt a new standard of data presentation that facilitates comparison of effects across the map. Evidence for sufficient effect size difference between the effects in structures of interest should be a prerequisite to the interpretation of spatial patterns of activation.