B1555
Title: Novel penalized regression method applied to study the association of brain functional connectivity and alcohol drinking
Authors: Jaroslaw Harezlak - Indiana University School of Public Health-Bloomington (United States) [presenting]
Mario Dzemidzic - Indiana University School of Medicine (United States)
David Kareken - Indiana University School of Medicine (United States)
Xiao Xu - Indiana University School of Public Health-Bloomington (United States)
Abstract: The intricate associations between brain functional connectivity and clinical outcomes are difficult to estimate. Common approaches do not account for the interrelated connectivity patterns in the functional connectivity (FC) matrix, which can jointly and/or synergistically affect the outcomes. In the application of a novel penalized regression approach called SpINNEr (sparsity-inducing nuclear norm estimator), brain FC patterns are identified that predict drinking outcomes. Results dynamically summarized in the R shiny app indicate that this scalar-on-matrix regression framework via the SpINNEr approach uncovers numerous reproducible FC associations with alcohol consumption.
