CORTICAL SURFACE FLATTENING: A QUASI-CONFORMAL APPROACH USING CIRCLE PACKINGS MONICA K. HURDAL1, KEN STEPHENSON2, PHILIP L. BOWERS1, DE WITT L. SUMNERS1, AND DAVID A. ROTTENBERG3;4 1Department of Mathematics, Florida State University, Tallahassee, FL 32306-4510, U.S.A. 2Department of Mathematics, University of Tennessee, Knoxville, TN 37996-1300, U.S.A. 3PET Imaging Center, VA Medical Center, Minneapolis, MN 55417, U.S.A. 4Departments of Neurology and Radiology, University of Minnesota, Minneapolis, MN 55455, U.S.A. Address for correspondence: Dr. Monica K. Hurdal, Department of Mathematics, Florida State University, Tallahassee, FL 32306-4510, U.S.A. Fax: (+1 850) 644-4053 Email:
[email protected] Running Title: Quasi-Conformal Flat Maps From Circle Packings Key Words: circle packing; conformal map; cortical flat map; mapping; Riemann Mapping Theorem; surface flattening 1 Abstract Comparing the location and size of functional brain activity across subjects is difficult due to individual differences in folding patterns and functional foci are often buried within cortical sulci. Cortical flat mapping is a tool which can address these problems by taking advantage of the two-dimensional sheet topology of the cortical surface. Flat mappings of the cortex assist in simplifying complex information and may reveal spatial relationships in functional and anatomical data that were not previously apparent. Metric and areal flattening algorithms have been central to brain flattening efforts to date. However, it is mathematically impossible to flatten a curved surface in 3-space without introducing metric and areal distortion. Nevertheless, the Riemann Mapping Theorem of complex function theory implies that it is theoretically possible to preserve conformal (angular) information under flattening.