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Abstract #0686

Brain Network Metric Derived from DWI: Application to the Limbic System

MAGNA25Luis Manuel Colon-Perez1, Caitlin Spindler2, Shelby Goicochea3, William Triplett4, Mansi Parekh5, Eric Montie6, Paul Richard Carney5, 7, Thomas Mareci4

1Physics, University of Florida, Gainesville, FL, United States; 2Biology, University of Florida; 3Chemistry, University of Florida; 4Biochemistry & Molecular Biology, University of Florida; 5Pediatrics, University of Florida; 6Science and Mathematics, University of South Carolina Beaufort, Bluffton, SC, United States; 7Wilder Center of Excellence for Epilepsy Research, University of Florida

MRI derived measurements such as brain network measures are inherently discrete and are affected by the resolution of acquisition. Appropriate normalization techniques permit the use of DWI and tractography methods to create measurements that would allow the study of the fibrous structure within the brain. Here we present an edge weight metric used to define the connectivity strength of a network node that would allow a better understanding of local networks in the brain. With this edge weight metric, anatomical structures are defined, i.e. nodes, and the implied white matter tracts from tractography give rise to the edge.