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Abstract #5482

Frequency Characteristics of Blind-Deconvolved Resting-State Networks using Empirical Mode Decomposition

Dietmar Cordes1,2, Muhammad Kaleem3, Xiaowei Zhuang1, Karthik Sreenivasan1, Zhengshi Yang1, Tim Curran2, 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

Energy-period relationships and frequency content of Intrinsic Mode Functions (IMFs) were studied in deconvolved fMRI data using a blind deconvolution method. Results are shown for multiband MB8 resting-state data collected with a TR of 0.765s for a group of 22 healthy subjects. Findings of the present study suggest that high-frequency content in the major primary resting-state networks (such as the Default Mode Network, Visual Network, Auditory Network, or Fronto-Parietal network) is rather limited and not supported to be of any significance for high frequencies larger than 0.21 Hz, whether in BOLD data or blind-deconvolved data.

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