基于分形特征的阿尔茨海默病脑网络结构分析

孙思翔; 李东艳

doi:10.11959/j.issn.2096-6652.202412

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基于分形特征的阿尔茨海默病脑网络结构分析

学术论文 | 更新时间：2024-11-04

- 基于分形特征的阿尔茨海默病脑网络结构分析
- Structural analysis of Alzheimer's disease brain networks based on fractal features
- 智能科学与技术学报 2024年6卷第3期页码：329-337
- 作者机构：
  
  大连交通大学软件学院，辽宁大连 116028
- 作者简介：
  
  [ "孙思翔（1999- ），男，大连交通大学软件学院硕士生，主要研究方向为复杂网络、分形与网络脆弱性。" ]
  [ "李东艳（1978- ），女，博士，大连交通大学软件学院副教授，主要研究方向为复杂网络、分形与网络脆弱性。" ]
- 基金信息：
  
  辽宁省教育厅基本科研项目(JYTMS20230011)
- DOI：10.11959/j.issn.2096-6652.202412
  中图分类号： TP399
- 收稿：2024-02-01，
  
  修回：2024-05-13，
  
  纸质出版：2024-09-15
- 稿件说明：
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孙思翔,李东艳.基于分形特征的阿尔茨海默病脑网络结构分析[J].智能科学与技术学报,2024,06(03):329-337.

SUN Sixiang,LI Dongyan.Structural analysis of Alzheimer's disease brain networks based on fractal features[J].Chinese Journal of Intelligent Science and Technology,2024,06(03):329-337.
孙思翔,李东艳.基于分形特征的阿尔茨海默病脑网络结构分析[J].智能科学与技术学报,2024,06(03):329-337. DOI： 10.11959/j.issn.2096-6652.202412.

SUN Sixiang,LI Dongyan.Structural analysis of Alzheimer's disease brain networks based on fractal features[J].Chinese Journal of Intelligent Science and Technology,2024,06(03):329-337. DOI： 10.11959/j.issn.2096-6652.202412.

摘要

阿尔茨海默病患者的功能脑网络在小世界及聚类系数等拓扑属性上与认知正常者存在差异。为进一步揭示阿尔茨海默病患者脑网络的结构特征及其与认知正常者脑网络结构的差异，引入分形特征进行对比分析。实验结果表明，阿尔茨海默病患者与认知正常者的脑网络在相同盒覆盖半径下的最小盒子数与连接比例存在显著差异。脑网络阈值为0.4时，认知正常者脑网络的连接比例值分布在区间[0

1]，而阿尔茨海默病患者脑网络的连接比例值分布在区间(0.5

1)。同时，不同阈值下，阿尔茨海默病患者脑网络的平均连接比例均高于认知正常者。上述网络结构差异可为阿尔茨海默病的诊断提供一种新参考。

Abstract

It had been demonstrated that the functional brain networks of Alzheimer’s patients exhibit topological properties distinct from those of cognitively normal individuals

including small-world and clustering coefficients. To further elucidate the structural characteristics of the brain networks of Alzheimer’s patients and their differences in brain network structure with cognitively normal individuals

fractal features were introduced for comparative analysis. Experimental results demonstrated a significant difference in the minimum number of boxes and connection ratio between brain networks of Alzheimer’s patients and cognitively normal individuals at the same box-covering radius. At the brain network threshold of 0.4

the connection ratio values of cognitively normal individuals’ brain networks were distributed in the [0

1] interval

while the connection ratio values of Alzheimer’s patients’ brain networks were distributed in the (0.5

1) interval. Furthermore

the average connection ratio of Alzheimer’s patients’ brain networks was found to be higher than that of cognitively normal individuals at different thresholds. These differences in network structure provide a new reference for the diagnosis of Alzheimer’s disease.

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references

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