Spatial normalization origins: Objectives, applications, and alternatives

Spatial normalization, in the context of human neuroimaging, is the selective removal of interindividual anatomical variance. The vast majority of the removed variance is attributable to differences in brain size and brain position within the imaging matrix. For this reason, even rather simple normalization algorithms [e.g., Fox et al., 19851 are surprisingly effective. Newer algorithms, such as those introduced in this issue by Friston et al. [1995] and Collins et al. [1995], remove the subtle but complex effects of shape variance, as well. Anatomical normalization allows images (or image-derived observations) from multiple subjects to be more accurately compared and combined. While alternatives can be posed (below), the 3-D neuroanatomical coordinate system introduced by Jean Talairach provides the most powerful and versatile general construct for spatial normalization. The three spatial normalization methods published in this issue [Collins et al, 1995; Friston et al., 1995; Lancaster et al., 19951 all fall within the broad domain originally defined by Talairach. Talairachs insight was that brain anatomy can be addressed using Cartesian coordinates. This concept was explained, implemented, validated and applied in the Atlas Stereotactique du Telencephale [1967]. The Atlas Stereotacfique is composed of five chapters. Chapter One introduces the concept of proportional normalization-scaling brains to a standard size-and describes the methods used to create the atlas. Chapter Two is the atlas proper, containing photographic plates of six human brains: two sectioned coronally, two sectioned axially and two sectioned sagittally. Prior to sectioning, each brain was rigidly registered, allowing their spatial relations to be preserved and 3-D coordinates to be applied. Chapters Three, Four, and Five can be viewed either as a series of validations of Talairachs spatial-normalization strategy, or, alternatively, as placing the first neural objects within a newly created 3-D model of the brain. The elegance of Talairachs concept is most powerfully revealed in Chapter Four, as Talairach reports spatial probability distributions for both anatomical and functional landmarks. Anatomical landmarks were defined by angiography and pneumoencephalography. Functional landmarks were defined by intraoperative cortical electrical stimulation. Much of the current work in our field can be considered refinements and applications of the concepts and procedures provided by Talairach. While Talairach has published two additional atlases [Talairach and Tournoux, 1988, 19951, the 1967 Atlns Stereotactique remains a landmark work. Application of Talairachs construct to functional neuroimages began rather slowly, but has steadily acquired acceptance. A fellow on sabbatical from Talairachs laboratory prompted Per Roland to use Talairachs mathematical terminology to report the results of a planar, 133Xe brain-activation study [Roland et al, 19801. In an effort to conform to the emerging standard, Fox and Raichle 119841 reported the first tomographic (PET) brain mapping observations within the Talairach space. After this normalization algorithm and its validations were published [Fox et al., 19851, Talairachs coordinates were adopted as the analytic and reporting standard for Raichle's laboratory, the first PET laboratory to do so. Transformation of entire images into the Talairach space-as opposed to computing the coordinates of activated locations-was first applied [Fox et al. 1986, Fig. 31 and then described IFox et al., 19881 by Fox, Mintun, Raichle and colleagues. These averaged images were the first of what have come to be termed statistical parametric maps or, more properly, statistical parametric images. The great improvement in statistical power made possible by intersubject image averagmg and facilitated by the distribution of software packages, such as SPM [Friston et al., 19911, for creating statistical parametric images have been instrumental in promoting the Talairach-space standard. The Talairach space is most properly viewed as a modeling construct, rather than as an atlas (or collection of atlases), a reporting standard, or a class of analytic algorithms. The modeling construct is a Carte-