Relating structural and functional connectivity to performance in a communication task

Authors:
Jeffrey T. Duda;Corey McMillan;Murray Grossman;James C. Gee
Affiliations:
Department of Bioengineering, University of Pennsylvania;Department of Neurology, University of Pennsylvania;Department of Neurology, University of Pennsylvania;Department of Radiology, University of Pennsylvania
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Year:
2010

Citing 2
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Direct Least Square Fitting of Ellipses

IEEE Transactions on Pattern Analysis and Machine Intelligence
Functional Connectivity: Integrating Behavioral, Diffusion Tensor Imaging, and Functional Magnetic Resonance Imaging Data Sets

Journal of Cognitive Neuroscience

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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.