STOR/Computational Med colloquium: Zhengwu Zhang, University of Rochester
University of Rochester
Statistical Analysis of Brain Structural Connectomes
There have been remarkable advances in imaging technology, used routinely and pervasively in many human studies, that non-invasively measures human brain structure and function. Among them, a particular imaging modality called diffusion magnetic resonance imaging (dMRI) is used to infer shapes of millions of white matter fiber tracts that act as highways for neural activity and communication across the brain. The collection of interconnected fiber tracts is referred to as the brain connectome. There is increasing evidence that an individual’s brain connectome plays a fundamental role in cognitive functioning, behavior, and the risk of developing mental disorders. Improved mechanistic understanding of relationships between brain connectome structure and phenotypes is critical to the prevention and treatment of mental disorders. However, progress in this area has been limited duo to the complexity of the data. In this talk, I will present challenges of analyzing such data and our recent progress, including connectome reconstruction and novel statistical modeling methods.
Refreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall