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Abstract #2324

Neurophysiological Basis of Multi-Scale Entropy Analysis of Brain Complexity and Its Relationship with Functional Connectivity

Danny JJ Wang1, Kay Jann1, Chang Fan1, Yang Qiao2, Yu-Feng Zang2, Hanbing Lu3, and Yihong Yang3

1Laboratory of FMRI Technology, Stevens Neuroimaging and Informatics Institute, University of Southern California (USC), Los Angeles, CA, United States, 2Center for Cognition and Brain Disorders, Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China, 3Neuroimaging Research Branch, National Institute on Drug Abuse, Baltimore, MD, United States

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of BOLD fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). We include both simulation data using neural mess model based brain network model and animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC.

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