Mathematical and Statistical Challenges in Neuroimaging Data Analysis (16w5036)


Hongtu Zhu (The University of North Carolina at Chapel Hill)

Brian Caffo (Johns Hopkins University)

Linglong Kong (University of Alberta)

(University of Victoria)

(Columbia University)


The Banff International Research Station will host the "Mathematical and Statistical Challenges in Neuroimaging Data Analysis" workshop from January 31st to February 5th, 2016.

Nowadays there is great need for the analysis of high dimensional, correlated, and complex neuroimaging data and clinical and genetic data obtained from various cross-sectional and clustered neuroimaging studies. These neuroimaging studies are essential to understanding the neural development of neuropsychiatric and neurodegenerative disorders, substance use disorders, the normal brain and the interactive effects of environmental and genetic factors on brain structure and function. The goal of this workshop is to bring together a diverse group of researchers from different disciplines including statistics, mathematics, computer science, biomedical engineering, psychiatry, psychology, neuroscience, and radiology, among other related sciences, to explore the common structure that underlies such methodologies, to discuss open problems, and to use this knowledge in turn to motivate and synthesize new avenues of research that will provide statistical tools that will help answer some of the biggest questions of modern science.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides
an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disc
iplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineeri
ng Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional
de Ciencia y Tecnología (CONACYT).