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Abstract #2268

Identifying Group Differences in Functional Subnetworks: A Novel Whole-Brain Method Applied to Dyslexia

Emily S. Finn1, Xilin Shen2, John M. Holahan3, Xenophon Papademetris2, 4, Dustin Scheinost4, Cheryl Lacadie2, Sally E. Shaywitz3, Bennett A. Shaywitz3, Robert Todd Constable2, 4

1Interdepartmental Neuroscience Program, Yale University, New Haven, CT, United States; 2Diagnostic Radiology, Yale University, New Haven, CT, United States; 3Yale Center for Dyslexia and Creativity, Yale University, New Haven, CT, United States; 4Biomedical Engineering, Yale University, New Haven, CT, United States

We applied a novel data-driven functional connectivity (FC) analysis to fMRI data from dyslexic vs. non-impaired readers to reveal functional subnetworks involved in successful reading. Our method improves upon previous FC analyses by not requiring a priori seed regions or arbitrary thresholds to determine connectivity. We found a network of occipitoparietal (visual association) and frontal (attention) areas that were better connected in non-impaired readers, suggesting that these subjects are better able to process word shapes and modulate their attention to visual stimuli. We believe this method can be extended to examine differentially connected functional subnetworks in other neural disorders.