title: Relating structural and functional connectivity to performance in a communication task.
abstract: Measures from event-related functional MRI, diffusion tensor imaging tractography and cognitive performance in a language-based task were used to test the hypothesis that both functional and structural connectivity provide independent and complementary information that aids in the identification of network components most related to the neurobiological basis for language and cognitive processing. Structural connectivity was measured by averaging fractional anisotropy (FA) over a geometric fiber bundle model that projects local white matter properties onto a centerline. In the uncinate fasciculus FA was found to predict performance on a measure of decision-making regarding homonym meaning. Functional synchronization of BOLD fMRI signals between frontal and temporal regions connected by the uncinate fasciculus was also found to predict the performance measure. Multiple regression analysis demonstrated that combining equidimensional measures of functional and structural connectivity identified the network components that most significantly predict performance.
authors.affiliation: Department of Bioengineering, University of Pennsylvania, USA. jtduda@seas.upenn.edu
authors.forename: Jeffrey T
authors.initials: JT
authors.lastname: Duda
authors.forename: Corey
authors.initials: C
authors.lastname: McMillan
authors.forename: Murray
authors.initials: M
authors.lastname: Grossman
authors.forename: James C
authors.initials: JC
authors.lastname: Gee
mesh_terms: D001931:Brain Mapping / Q000379:methods; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007802:Language; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009434:Neural Pathways / Q000033:anatomy & histology* / Q000502:physiology*; D013647:Task Performance and Analysis