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基于能量景观的阿尔茨海默病三重网络分析

Triple-network analysis of Alzheimer's disease based on the energy landscape.

作者信息

Li Youjun, An Simeng, Zhou Tianlin, Su Chunwang, Zhang Siping, Li Chenxi, Jiang Junjie, Mu Yunfeng, Yao Nan, Huang Zi-Gang

机构信息

The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi, China.

Research Center for Brain-inspired Intelligence, Xi'an Jiaotong University, Xi'an, Shaanxi, China.

出版信息

Front Neurosci. 2023 May 23;17:1171549. doi: 10.3389/fnins.2023.1171549. eCollection 2023.

DOI:10.3389/fnins.2023.1171549
PMID:37287802
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10242117/
Abstract

INTRODUCTION

Research on the brain activity during resting state has found that brain activation is centered around three networks, including the default mode network (DMN), the salient network (SN), and the central executive network (CEN), and switches between multiple modes. As a common disease in the elderly, Alzheimer's disease (AD) affects the state transitions of functional networks in the resting state.

METHODS

Energy landscape, as a new method, can intuitively and quickly grasp the statistical distribution of system states and information related to state transition mechanisms. Therefore, this study mainly uses the energy landscape method to study the changes of the triple-network brain dynamics in AD patients in the resting state.

RESULTS

AD brain activity patterns are in an abnormal state, and the dynamics of patients with AD tend to be unstable, with an unusually high flexibility in switching between states. Also , the subjects' dynamic features are correlated with clinical index.

DISCUSSION

The atypical balance of large-scale brain systems in patients with AD is associated with abnormally active brain dynamics. Our study are helpful for further understanding the intrinsic dynamic characteristics and pathological mechanism of the resting-state brain in AD patients.

摘要

引言

静息状态下的脑活动研究发现，大脑激活集中在三个网络周围，包括默认模式网络（DMN）、突显网络（SN）和中央执行网络（CEN），并在多种模式之间切换。阿尔茨海默病（AD）作为老年人的常见疾病，会影响静息状态下功能网络的状态转换。

方法

能量景观作为一种新方法，可以直观快速地掌握系统状态的统计分布以及与状态转换机制相关的信息。因此，本研究主要采用能量景观方法来研究AD患者静息状态下三网络脑动力学的变化。

结果

AD患者的脑活动模式处于异常状态，AD患者的动力学往往不稳定，状态之间的切换具有异常高的灵活性。此外，受试者的动态特征与临床指标相关。

讨论

AD患者大脑系统的非典型平衡与异常活跃的脑动力学有关。我们的研究有助于进一步了解AD患者静息状态下大脑的内在动态特征和病理机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9170/10242117/1fc53466b61f/fnins-17-1171549-g009.jpg
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