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 Zhong^1,4, Giovanni Schifitto^4,5, 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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