A1277
Title: Fiber tract microstructural quantile (FMQ) regression for white matter tracts
Authors: Zhou Lan - Brigham and Women\'s Hospital, Harvard Medical School (United States) [presenting]
Abstract: The brain's white matter is critical for cognition. A new approach for statistical analysis of white matter fiber tracts, fiber tract microstructural quantile (FMQ) regression, is introduced. The method employs the statistical technique of quantile regression with clustered data to investigate the relationship between fiber tract tissue microstructure and clinical or psychological covariates. To demonstrate the proposed approach, an illustrative study is provided based on the data of a large dataset, human connectome project-young adult (HCP-YA), with a focus on specific tracts expected to relate to particular aspects of motor function and cognition as described in a recent review. The cohort of 809 participants is used for the illustrative study. The arcuate fasciculus (AF), uncinate fasciculus (UF), Cingulum (CB), and corticospinal tract (CST) were selected to investigate their associations with scalar factors of language, memory, executive function, and motor, respectively. The illustrative study results follow the previously established findings and imply that our proposed profile is more powerful in identifying significance than the methods compared. Moreover, it is demonstrated that using the quantile profile might be more anatomically insightful in providing microstructural inference for investigating the association between scalar factors and white matter tracts.
