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Abstract #3454

Multiscale sample entropy analysis of resting-state fMRI over the lifespan

Dilmini Wijesinghe1, Danny JJ Wang1, and Kay Jann1
1USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine at USC, Los Angeles, CA, United States

Synopsis

Keywords: fMRI Analysis, Data Analysis, Multiscale Sample Entropy, Complexity

Motivation: Multiscale sample entropy (MSE) is a common complexity metric used in functional Magnetic Resonance Imaging (fMRI), yet it has not been applied to analyze the evolution across age groups.

Goal(s): The goal of this study is to analyze the evolution of fMRI complexity over the lifespan using MSE.

Approach: Resting-state fMRI data of 526 subjects age 6 – 85 years were analyzed with a linear mixed-effect model (LME) of MSE in different brain regions.

Results: Overall, a decrease in mean gray matter complexity was observed after puberty. LME model showed significant decrease in complexity with age in middle frontal and superior frontal gyrus.

Impact: The findings of this study shed light on the evolution of brain complexity with development and aging and may provide benchmark for detecting aberrant complexity in brain disorders.

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