Trajectories of brain entropy across lifetime estimated by resting state functional magnetic resonance imaging

The human brain is a complex system of interconnected brain regions that form functional networks with differing roles in cognition and behavior. However, the trajectories of these functional networks across development are unclear and designing a metric to track the complex trajectory of these char...

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Published inHuman brain mapping Vol. 43; no. 14; pp. 4359 - 4369
Main Authors Niu, Yan, Sun, Jie, Wang, Bin, Yang, Yanli, Wen, Xin, Xiang, Jie
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.10.2022
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Summary:The human brain is a complex system of interconnected brain regions that form functional networks with differing roles in cognition and behavior. However, the trajectories of these functional networks across development are unclear and designing a metric to track the complex trajectory of these characteristics throughout the lifespan is challenging. Here, permutation entropy (PE) was used to examine age‐related variations in functional magnetic resonance imaging (fMRI) in healthy subjects aged 6–85 from global, network, and nodal perspectives. The global PE followed an inverted U‐shaped trajectory that peaked at approximately age 40. The trajectory of the motor and somatosensory functional network was more consistent with a linear model and increased with age; other functional networks showed inverted U‐shaped trajectories that peaked between 25 and 52 years of age. All nodes showed inverted U‐shaped trajectories. Using cluster analysis, the peak ages of nodes were grouped into three clusters (at 24, 38, and 51 years). Overall, we characterized four aging trajectories: networks with a linear increase, early peak age, intermediate peak age, and older peak age. These findings suggest possible complexity in trajectories at critical age points regarding changes in related functional brain networks.
Bibliography:Funding information
Yan Niu and Jie Sun are the co‐first authors.
the National Key R & D Program of China, Grant/Award Number: 2018AAA0102601; the National Natural Science Functional of China, Grant/Award Numbers: 61873178, 61876124, 61906130, 62176177; the Shanxi Province Application Basic Research Plan, Grant/Award Numbers: 20210302123099, 20210302124550; the Shanxi Provincial International Cooperation Foundation, Grant/Award Number: 201803D421047
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Funding information the National Key R & D Program of China, Grant/Award Number: 2018AAA0102601; the National Natural Science Functional of China, Grant/Award Numbers: 61873178, 61876124, 61906130, 62176177; the Shanxi Province Application Basic Research Plan, Grant/Award Numbers: 20210302123099, 20210302124550; the Shanxi Provincial International Cooperation Foundation, Grant/Award Number: 201803D421047
ISSN:1065-9471
1097-0193
1097-0193
DOI:10.1002/hbm.25959