A Connectome Wide Functional Signature of Transdiagnostic Risk for Mental Illness
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Background High rates of comorbidity, shared risk, and overlapping therapeutic mechanisms have led psychopathology research towards transdiagnostic dimensional investigations of clustered symptoms. One influential framework accounts for these transdiagnostic phenomena through a single general factor, sometimes referred to as the ‘p’ factor, associated with risk for all common forms of mental illness. Methods Here we build on past research identifying unique structural neural correlates of the p factor by conducting a data-driven analysis of connectome wide intrinsic functional connectivity (n = 605). Results We demonstrate that higher p factor scores and associated risk for common mental illness maps onto hyper-connectivity between visual association cortex and both frontoparietal and default mode networks. Conclusions These results provide initial evidence that the transdiagnostic risk for common forms of mental illness is associated with patterns of inefficient connectome wide intrinsic connectivity between visual association cortex and networks supporting executive control and self-referential processes, networks which are often impaired across categorical disorders.
Published Version (Please cite this version)
Elliott, ML, A Romer, AR Knodt and AR Hariri (2018). A Connectome Wide Functional Signature of Transdiagnostic Risk for Mental Illness. Biological Psychiatry. 10.1016/j.biopsych.2018.03.012 Retrieved from https://hdl.handle.net/10161/16709.
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Max is a clinical psychology PhD student working with Ahmad Hariri and the Moffitt & Caspi lab after completing his BS at the University of Minnesota and spending two years as a research fellow at the National Institute of Mental Health. Max is interested in further understanding the structure of mental illness through investigating the interacting relationships between genes, environment and the brain. He is particularly interested in finding ways to combine knowledge about genetics and lifespan development with brain imaging to better assess and understand risk factors for mental illness. Through the use of imaging endophenotypes he hopes to further map out relationships between individual differences in health and disease.
Integrating psychology, neuroimaging, pharmacology and molecular genetics in the search for biological pathways mediating individual differences in behavior and related risk for psychopathology.
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