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    Resting-State Functional Brain Networks in Bipolar Spectrum Disorder: A Graph Theoretical Investigation

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    Genre
    Thesis/Dissertation
    Date
    2016
    Author
    Black, Chelsea Lynn
    Advisor
    Alloy, Lauren B.
    Committee member
    Giovannetti, Tania
    Chein, Jason M.
    Chen, Eunice Y.
    McCloskey, Michael S.
    Olino, Thomas
    Olson, Ingrid R.
    Department
    Psychology
    Subject
    Psychology
    Psychology, Clinical
    Neurosciences
    Bipolar Disorder
    Fmri
    Graph Theory
    Resting-state
    Reward Sensitivity
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/809
    
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    DOI
    http://dx.doi.org/10.34944/dspace/791
    Abstract
    Neurobiological theories of bipolar spectrum disorder (BSD) propose that the emotional dysregulation characteristic of BSD stems from disrupted prefrontal control over subcortical limbic structures (Strakowski et al., 2012; Depue & Iacono, 1989). However, existing neuroimaging research on functional connectivity between frontal and limbic brain regions remains inconclusive, and is unable to adequately characterize global functional network dynamics. Graph theoretical analysis provides a framework for understanding the local and global connections of the brain and comparing these connections between groups (Sporns et al., 2004). The purpose of this study was to investigate resting state functional connectivity in individuals at low and high risk for BSD based on moderate versus high reward sensitivity, both with and without a BSD diagnosis, using graph theoretical network analysis. Results demonstrated decreased connectivity in a cognitive control region (dorsolateral prefrontal cortex), but increased connectivity of a brain region involved in the detection and processing of reward (bilateral orbitofrontal cortex), among participants at high risk for BSD. Participants with BSD showed increased inter-module connectivity of the dorsal anterior cingulate cortex (ACC). Reward sensitivity was associated with decreased global and local efficiency, and interacted with BSD risk group status to predict inter-module connectivity. Findings are discussed in relation to neurobiological theories of BSD.
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