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Abstract #3965

Surface Based Connectivity Integration – A Processing Pipeline for High Resolution Integration of Structural and Functional Connectivity

Kyle Murray1, Martin Cole2, Etienne St-Onge3, Maxime Descouteaux3, Jianhui Zhong1,4, Giovanni Schifitto4,5, and Zhengwu Zhang2
1Physics and Astronomy, University of Rochester, Webster, NY, United States, 2Biostatistics and Computational Biology, University of Rochester, Rochester, NY, United States, 3Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada, 4Imaging Sciences, University of Rochester, Rochester, NY, United States, 5Neurology, University of Rochester, Rochester, NY, United States

The integration of structural and functional connectivity thus far has been limited to atlas-based parcellation studies. We present a novel atlas-free processing pipeline to explore the integration of structural and functional connectivity at high spatial resolution. This pipeline has been reliably replicated in other research subjects. We also introduce a dual-modality imaging feature that can be mapped to the gray-white matter surfaces. Early results demonstrate that structural and functional connectivity are likely strongly linked. This pipeline allows for the first time to perform connectivity analyses on individual white surfaces, opening up many more possibilities to future connectivity studies.

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