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Abstract #1610

The Spectral Power of Brain Oscillations Predicts the Functions of Brain Networks

Yi Chia Li1, Jyh Horng Chen2

1Graduate Institute of Biological Engineering & Bioinformatics, National Taiwan University, Taipei, Taiwan; 2Interdisciplinary MRI/MRS Lab, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan

Up to 10 functional networks contributed by low frequency fluctuations (LFFs) have been reliably identified to consistently exist in human resting brains. These networks consist of regions which are known to be involved in function of motor, vision, execution, auditory, pain perception, language, cerebellum, and the so called default-mode network (DMN). Based on the concept proposed by Weisskoff et al. that the baseline of LFF power spectrums followed a 1/f curve, we analyzed resting-state fMRI data of 11 healthy participants with 1/f model, to further investigate the spectral characteristics of brain oscillations across different networks. The parameter b in 1/f model was discovered to predict the functions of these networks, which illustrated the spectral power of brain oscillations differed across networks which served different functions such as sensory, active, cognition, and default-mode. The result was supported by the discovery of the prior literature that the spectral characteristics of brain oscillations linked with neural processes which were modulated by the functions of brain networks.