Coordinate‐based voxel‐wise meta‐analysis: Dividends of spatial normalization. Report of a virtual workshop

摘要

Spatial normalization transforms a brain image from its natural form (“native space”) into a standardized form defined by a reference brain [Fox, ]. The original motivation for introducing this technique was to allow the brain locations of task‐induced functional activations to be reported in a “precise and unambiguous” manner, thereby “facilitating direct comparison of experimental results from different laboratories” [Fox et al., ]. The prospect of clear communication as a “dividend” from a community commitment to spatial normalization, however, proved largely unconvincing to the still‐nascent brain mapping community of the middle 1980s. Improvement in the signal‐to‐noise ratio of functional brain maps that could be achieved by intersubject image averaging in standardized space [Fox et al., ; Friston et al., ] proved to be a very salient motivation, leading to widespread adoption of this data analysis standard. We estimate the human functional brain mapping (HFBM) literature reporting brain activations as x‐y‐z coordinates in standardized space to be no less than 2,500 articles (∼10,000 experiments) with ∼500 new articles (2,000 experiments) published per year (Fig. ). Fortunately, regardless of the motivation for adoption of this standard, the widespread use of spatial standardization makes the HFBM literature fertile ground for quantitative meta‐analysis methods based on spatial concordance [Fox and Lancaster, , ; Fox et al., ]. In reference to the title of this article, voxel‐based, function‐location meta‐analysis can be considered a dividend that the HFBM community is now receiving from its long‐term investment in the development and promulgation of community standards for data‐analysis and, in particular, spatial normalization.