Abstract #0686

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

Luis 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.