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Open AccessArticle

A Generative Network Model of the Human Brain Normal Aging Process

School of Computer Science and Engineering, Northeastern University, Shenyang 110000, China
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Symmetry 2020, 12(1), 91; https://doi.org/10.3390/sym12010091
Received: 16 November 2019 / Revised: 20 December 2019 / Accepted: 24 December 2019 / Published: 3 January 2020
The human brain is approximately a symmetric structure, although the functional brain does not exhibit symmetry. Functional brain aging process modelling is essential for the understanding of hypothesized generative mechanisms for human brain networks throughout one’s lifespan. We present a novel generative network model of the human functional brain network, which is the hybrid of the local naïve Bayes model and the anatomical similarity correction (LNBE). We use LNBE, as well as published generative network models to simulate the aging process of the functional brain network, to construct artificial brain networks and to reveal the generative mechanisms and evolutionary patterns of human functional brain across human lifespans. It is suggested that the idea of classifying common neighbours while considering anatomical distances during network formation can provide a much more similar generative mechanism of the human fMRI brain aging process as well as a more practical generative network model of it. We hold that studies on brain normal aging process modelling have the potential to improve the way in which early warnings for latent injury or disease are practised today and advance healthcare. View Full-Text
Keywords: graph theory; fMRI; functional brain network; generative network model; brain aging modelling graph theory; fMRI; functional brain network; generative network model; brain aging modelling
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Liu, X.; Si, S.; Hu, B.; Zhao, H.; Zhu, J. A Generative Network Model of the Human Brain Normal Aging Process. Symmetry 2020, 12, 91.

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