Connectivity based segmentation of the periaqueductal grey matter in humans with diffusion tensor imaging

Introduction The midbrain periaqueductal gray matter (PAG) is involved in a number of key homeostatic neurobiological functions, such as pain modulation and cardiorespiratory control. Currently, most of our understanding of its structure and function comes from animal research, and the translation of these findings to humans has yet to be accomplished non-invasively. Despite its cytoarchitectonic (and MRI) homogeneity, animal models have shown significant heterogeneity with respect to functional properties, anatomical connections and chemical properties between subdivisions of the PAG. These subdivisions are proposed as four longitudinal columns parallel to the aqueduct, and their identification in vivo is critical to improving our understanding of the PAG and its use in interventional therapies such as deep brain stimulation (DBS). Previous attempts to segment the human PAG have yielded disappointing results, in part due to its small size and location. This study used high resolution diffusion tensor imaging (DTI) to segment the PAG based upon voxel connectivity profiles.