Improved agreement between Talairach and MNI coordinate spaces in deep brain regions

Disagreement between the Talairach atlas and the stereotaxic space commonly used in software like SPM is a widely recognized problem. Others have proposed affine transformations to improve agreement in surface areas such as Brodmann's areas. This article proposes a similar transformation with the goal of improving agreement specifically in the deep brain region. The task is accomplished by finding an affine transformation that minimizes the mean distance between the surface coordinates of the lateral ventricles in the Talairach atlas and the MNI templates. The result is a transformation that improves deep brain agreement over both the untransformed Talairach coordinates and the surface-oriented transformation. While the transformation improves deep brain agreement, surface agreement is generally made worse. For areas near the lateral ventricle, the transformation presented herein is valuable for applications such as region of interest (ROI) modeling.