Research

A Group Averaged Tractography Atlas

We introduced an expert-vetted, population-based atlas of the structural connectome derived from diffusion MRI data (N=842). This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate 550,000 trajectories of representative white matter fascicles. The trajectories were clustered and labeled by a team of experienced neuroanatomists. Multi-level network topology was illustrated by connectograms of the whole brain, subdivisions in the association, projection, and commissural pathways, and individual fiber bundles. This atlas of the structural connectome represents normative neuroanatomical organization of human brain white matter, complimentary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectomic studies as well as clinical and educational applications.

Neuroanatomy Studies using Advanced Diffusion MRI Fiber Tracking

Conventional diffusion MRI methods rely on diffusivity-based measurement (e.g. fractional anisotropy) to guide a fiber tracking algorithm, but this approach has suffered poor accuracy due to the partial volume effect. To achieve a better accuracy, we developed generalized q-sampling imaging and its derived fiber tracking method, which used density-based measurement to guide a fiber tracking algorithm. This fiber tracking method was examined in an open competition held by the International Society for Magnetic Resonance in Medicine (ISMRM). A total of 20 groups all over the world submitted 96 different approaches. Our method have achieved the highest valid connection score (92.49%, ID#03), whereas other methods have valid connections around 60~80%, showing that density-based measurement can greatly improve the accuracy of diffusion MRI fiber tracking. We utilized this high accuracy fiber tracking method to study neuroanatomy and reveal the structural organization of the human brain.

DSI Studio—An Integrative Platform for Diffusion MRI Analysis

Mapping the trajectories of human connectome and explore its properties is one of the largest endeavors in neuroscience. DSI Studio is an open source diffusion MRI analysis tool that maps brain connections, characterizes their biophysical metrics, and correlates the metrics with neuropsychological variables. It is a collective implementation of diffusion MRI methods and has established its unique scientific impact. Since its debut in 2008, DSI Studio has been downloaded more than 20,000 times. The user groups are around major universities and hospitals in the US and all over the world. They have used DSI Studio in human and animal studies to investigate how major fiber pathways are affected by neurological and psychiatric diseases. A complete list of peer-review publications using DSI Studio can be found at http://dsi-studio.labsolver.org/publications

Local Connectome Fingerprint

We are investigating local connectome and its association with neuropsychological factors. The local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size) within a voxel, and it reflects the proximal characteristics of white matter fascicles distributed throughout the brain. They show how variability in the local connectome is correlated in a principled way across individuals. This intersubject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This shows, for the first time, how the local connectome has both the sensitivity and the specificity to be used as a phenotypic marker for subject-specific attributes.