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Abstract #0907

Characterizing Hierarchical Spatial Variations of the Brain: A Novel Analysis Framework to Study Dynamic Brain Function

Armin Iraji1, Zening Fu1, Eswar Damaraju1, Thomas P. DeRamus1, Noah Lewis1, Juan R. Bustillo2, Rhoshel K. Lenroot2, Ayse Belger3, Judy M. Ford4,5, Sarah McEwen6, Daniel Mathalon4,5, Bryon Mueller7, Godfrey D. Pearlson8, Steven G. Potkin9, Adrian Preda9, Jessica Turner10, Jatin Vaidya11, Theo G.M. van Erp12, and Vince D. Calhoun1,8,13

1The Mind Research Network, Albuquerque, NM, United States, 2Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, United States, 3Department of Psychiatry, University of North Carolina, Chapel Hill, NC, United States, 4Department of Psychiatry, University of California San Francisco, San Francisco, CA, United States, 5San Francisco VA Medical Center, San Francisco, CA, United States, 6Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States, 7Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States, 8School of Medicine, Yale University, New Haven, CT, United States, 9Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, United States, 10Department of Psychology, Georgia State University, Atlanta, GA, United States, 11Department of Psychiatry, University of Iowa, Iowa, IA, United States, 12Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, United States, 13Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States

A novel, data-driven analysis framework was proposed to characterize the spatial variation of brain function. This framework utilizes the concept of a functional hierarchy and encapsulates the spatiotemporal variations of brain functional domains from its associated high-order intrinsic connectivity networks. The results show spatial fluidity behavior of functional domains, including a broad spectrum of changes in regional associations from strong coupling to complete decoupling. Interestingly, such spatial variations drive the interactions between functional domains, showing concurrent evaluation in time. Our results further highlight that the captured spatial dynamics can serve as potential biomarkers for patients with schizophrenia.

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