Abstract
Diffusion-weighted magnetic resonance imaging and computational tractography are unique methods to measure the white matter in living brains. In the decade since their development, these methods revolutionized our understanding of the importance of the human white-matter for health and disease. Critical to the study of the white matter is the quantification of the confidence in the estimated fascicles and statistical testing of neuroanatomical hypotheses about connectivity. We will present a technology, called LiFE, to perform both validation and statistical inference on living connectomes. This new method improves upon the current state-of-the-art in fundamental ways and can be applied to any type of diffusion data in human and animal brains. We measured diffusion MRI at high spatial (1.5 mm isotropic) and angular resolution (96 diffusion directions). We used constrained spherical deconvolution and probabilistic tractography (Tournier et al., 2012) to generate candidate connectomes. Tractography takes diffusion data as input and estimates white-matter fascicles as output - the candidate connectome. LiFE takes the candidate connectome as input and predicts diffusion data as output. LiFE identifies the fascicles contributing to predicting the diffusion data and eliminates the rest as false connections. We used the technology to identify a major white-matter pathway communicating information between the dorsal and ventral visual streams; the Vertical Occipital Fasciculus (VOF). This pathway is large and its organization establishes that the human ventral and dorsal visual streams communicate substantial information through areas V3A/B and hV4/VO-1. We suggest that the VOF is crucial for transmitting signals between regions that encode object properties including form, identity and color information and regions that map spatial location to action plans. Our results provide novel ways to study the network of white-matter connections in the living brain and important insights on the organization of the visual field maps.
Meeting abstract presented at VSS 2014