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001022040 1001_ $$0P:(DE-Juel1)178611$$aJung, Kyesam$$b0$$eFirst author
001022040 245__ $$aSimulated brain networks reflecting progression of Parkinson’s disease
001022040 260__ $$aCold Spring Harbor$$bCold Spring Harbor Laboratory, NY$$c2024
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001022040 520__ $$aNeurodegenerative progression of Parkinson’s disease affects brain structure and function and, concomitantly, alters topological properties of brain networks. The network alteration accompanied with motor impairment and duration of the disease is not yet clearly demonstrated in the disease progression. In this study, we aim at resolving this problem with a modeling approach based on large-scale brain networks from cross-sectional MRI data. Optimizing whole-brain simulation models allows us to discover brain networks showing unexplored relationships with clinical variables. We observe that simulated brain networks exhibit significant differences between healthy controls (n=51) and patients with Parkinson’s disease (n=60) and strongly correlate with disease severity and disease duration of the patients. Moreover, the modeling results outperform the empirical brain networks in these clinical measures. Consequently, this study demonstrates that utilizing simulated brain networks provides an enhanced view on network alterations in the progression of motor impairment and potential biomarkers for clinical indices.
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001022040 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon$$b1
001022040 7001_ $$0P:(DE-HGF)0$$aCaspers, Julian$$b2
001022040 7001_ $$0P:(DE-Juel1)131880$$aPopovych, Oleksandr$$b3$$eCorresponding author
001022040 773__ $$0PERI:(DE-600)2766415-6$$a10.1101/2024.01.12.574450$$tbioRxiv beta$$y2024
001022040 8564_ $$uhttps://www.biorxiv.org/content/10.1101/2024.01.12.574450v1
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