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Abstract #1841

Gray Matter Network Organization in Psychotic Disorders

Wenjing Zhang1, Du Lei1, Brett Clementz2, Carol Tamminga3, Matcheri Keshavan4, Sarah Keedy5, Godfrey Pearlson6, Elliot Gershon5, Jeffrey Bishop7, Jieke Liu1, Qiyong Gong1, John Sweeney8, and Su Lui1

1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 2Department of Psychology, University of Georgia, Athens, GA, United States, 3Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States, 4Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, 5Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States, 6Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, United States, 7Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States, 8Department of Psychiatry, University of Cincinnati, Cincinnati, OH, United States

Recently, new approaches have been developed using graph theory to identify deficits in gray matter networks at individual level. In the current study, by investigating single-subject graphs based on gray matter morphology to define neuroanatomic networks in a large group of individuals across psychotic disorders (n=330), we observed disrupted network organizations associated with superior temporal and prefrontal regions within the gray matter networks in patients, which were also negatively associated with severity of psychotic symptoms. These findings showed the utility of graph theory based measures of neuroanatomic network organization to extend our understanding of the neurobiology underlying psychotic disorders.

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