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Abstract #0421

Early Stage Parkinson’s Disease Shows Changes in Energy and Period Content of Resting-State Networks

Dietmar Cordes1,2, Muhammad Kaleem3, Xiaowei Zhuang1, Karthik Sreenivasan1, Zhengshi Yang1, Sarah Banks1, Brent Bluett1, Zoltan Mari1, and Virendra Mishra1

1Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States, 2University of Colorado, Boulder, CO, United States, 3University of Management & Technology, Lahore, Pakistan

Low-frequency BOLD fluctuations of major resting-state networks in early Parkinson’s disease (PD) were studied and compared with matched normal controls. Empirical Mode Decomposition (EMD) was used to decompose the natural occurring frequency bands of major brain resting-state networks. The novelty of our approach lies in the data-adaptive decomposition of fMRI data using EMD, and identification of resting-state networks based on energy and period (inverse frequency) characteristics of intrinsic mode functions. For most networks studied that showed a large effect size, the frequency content of the associated network time series was found to be significantly reduced in PD.

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